Database

Database Engineer Jobs

2,027 jobs found

8d ago

Data Engineer - Mid Level

USAA Plano, TX

Plano, TX

8d ago

$103k - $198k/yr Full time Big Data Cloud Data Warehouse Cloud Data Warehouse

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Job Description

Data Engineer role (Mid Level) with USAA in a hybrid setting in Plano, TX 75024. You will design and deliver data engineering solutions end to end, partnering with stakeholders to align analytic systems with business objectives. The focus includes modern platforms and tools such as Snowflake, dbt, SQL, Kafka, Python, and data integration technologies.

What you can expect

Work across the full data management lifecycle, from requirements and analysis through pipeline engineering, testing, deployment, scheduling, and production support.
Design and implement complex technical solutions for data engineering and analytic systems.
Identify and address major technical problems and architecture gaps, including design, security, and performance considerations.
Translate business features into technical stories and delivery approaches.
Influence stakeholders through technical adoption of best-fit solutions.
Build proof of concepts and prototypes to support complex initiatives.
Collaborate with engineers on new technologies and alternatives for planning and execution.
Support onboarding of entry level engineers and may mentor junior engineers.

Core responsibilities

Acquire data from multiple sources and maintain databases, data warehouses, and/or data lakes.
Develop, maintain, and enforce data development tools and standards.
Conduct regular code reviews to improve quality and ensure compliance.
Ensure risks tied to business activities are identified, measured, monitored, and controlled in line with risk and compliance policies and procedures.
Participate in design reviews by sharing feedback on trends and recommending solutions.

Skills and qualifications

Bachelor’s degree; or 4 years of relevant education and/or experience.
4 years of data engineering, data analysis, or software development experience implementing data solutions, including at least 1 year focused on data engineering or data management.
Extensive knowledge and working experience with SQL and relational databases.
Understanding of Agile methodology practices.
Strong analytical and problem-solving skills.
Proficiency working with cloud technologies and tools.

Tools and technologies

Snowflake, dbt, SQL, Kafka, APIs, Python, Data Modeling, Fivetran, Git/version control

Compensation and location

Location: Plano, TX 75024 (hybrid). Also available: Charlotte, NC; Phoenix, AZ; San Antonio, TX.
Salary range: USD 103,450 - 197,730 per year.
USAA uses an effective process to assess market data and set ranges; your pay is based on experience and market data, and actual salary may vary by location.
Employees may be eligible for pay incentives based on corporate and individual performance at the discretion of the USAA Board of Directors.

Benefits

Comprehensive medical, dental, and vision plans
401(k)
Pension
Life insurance
Parental benefits
Adoption assistance
Paid time off program with paid holidays plus 16 paid volunteer hours
Various wellness programs
Career path planning and continuing education

Additional details

Job ID: R0121997
Date posted: 10/26/2026
Application status: Accepted on an ongoing basis and will remain open until filled. Apply as soon as possible, including the same day you view the posting.
Equal Opportunity Employer: USAA provides equal employment consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.
Visa sponsorship: USAA does not provide visa sponsorship for this role. Please do not apply if you will need immigration support now or in the future (for example, H-1B, TN, STEM OPT Training Plans, etc.).

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8d ago

Data Engineer

TG Administration LLC Scottsdale, AZ

Scottsdale, AZ

8d ago

Full time Backend Developer Azure Azure Data Engineer

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Job Description

TG Administration LLC is seeking a Data Engineer to design, build, and maintain scalable data integration pipelines and Azure data architectures. The role focuses on governed data flows using a medallion approach to support analytics and downstream applications.

Responsibilities

Design, develop, and maintain end-to-end data pipelines to ingest data from internal and external systems into Azure data platforms
Build and manage data integration processes using tools such as Azure Data Factory, Azure Synapse, and/or Azure Data Lake
Implement and enforce medallion architecture (bronze, silver, gold) for structured refinement and consumption of data
Transform raw data into clean, validated, and enriched datasets for analytics and business use
Develop and optimize data models and transformation logic to support performance and scalability
Integrate data from APIs, SaaS platforms, databases, and third-party systems
Ensure data quality, consistency, and integrity across all pipeline stages
Implement monitoring, alerting, and logging for pipeline performance and failures
Collaborate with data analysts, data scientists, and product teams to support reporting and advanced analytics needs
Maintain and optimize data storage solutions (for example, Azure Data Lake and Synapse) to improve cost and performance efficiency
Establish and follow best practices for version control, CI/CD, and deployment of data pipelines
Document data flows, transformations, and system dependencies

Requirements

3+ years of experience in data engineering, ETL/ELT development, or data integration
Hands-on experience building and maintaining production-grade data pipelines
Experience working within cloud-based data platforms (Azure preferred)
Strong proficiency in SQL and data transformation techniques
Experience with Azure data services including Azure Data Factory, Azure Data Lake, and Synapse Analytics
Expertise in ETL/ELT pipeline design and orchestration
Strong understanding of data modeling (relational and dimensional)
Experience working with APIs, file-based ingestion, and streaming data sources
Knowledge of data quality, validation, and error-handling techniques
Strong problem-solving and troubleshooting skills
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field
Equivalent combination of education and experience may be considered

Technologies

Azure
Azure Data Factory
Azure Synapse
Azure Data Lake
Synapse Analytics
SQL
ETL/ELT
APIs
SaaS
PySpark
Spark
Databricks
Delta Lake
CI/CD
DevOps

Preferred Qualifications

Experience implementing medallion architecture (bronze/silver/gold layers)
Experience integrating multiple enterprise systems (CRM, ERP, SaaS platforms)
Experience supporting analytics or BI environments

Preferred Knowledge and Skills

Experience with PySpark, Spark, or Databricks
Familiarity with Delta Lake and lakehouse architectures
Experience with CI/CD pipelines and DevOps practices in Azure
Knowledge of data governance, lineage, and cataloging tools
Experience optimizing performance and cost in cloud environments

Benefits

Healthcare Benefits – Medical, Dental, and Vision coverage
Retirement Benefits – 401(k) with employer match (19 years of age and older)
Time Off – Paid time off (PTO) and leaves of absence, in accordance with applicable law and eligibility criteria

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8d ago

Data & Analytics Engineer

Texas State Technical College Texas

Texas

8d ago

Full time Artificial Intelligence Business Intelligence Cloud Data Engineering

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Job Description

The Data & Analytics Engineer provides hands-on development of data, analytics, business intelligence, and data science solutions to support institutional decision-making and day-to-day operations. The role partners across the analytics lifecycle using Microsoft Fabric and Power BI, and applies advanced analytics and AI expertise when needed.

Responsibilities

Designs, develops, and maintains scalable data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies.
Transforms raw and complex source data into analytics-ready datasets to support institutional reporting, business intelligence, advanced analytics, and data science initiatives.
Develops and maintains analytical data models, data transformations, automated pipelines, notebooks, and reusable data assets, coordinating with Data Engineering to manage Silver and Gold architectural layers.
Applies software and data engineering practices including version control, testing, technical documentation, code reviews, and deployment management while troubleshooting and optimizing for performance, reliability, and maintainability.
Designs and delivers enterprise Power BI dashboards, reports, semantic models, and analytical tools that support institutional decision-making.
Builds and maintains reusable semantic models, standardized measures, and institutional performance metrics using Power BI, DAX, Power Query, and Microsoft Fabric.
Implements best practices for data visualization, dimensional modeling, performance tuning, row-level security, and report lifecycle management.
Partners with Data Governance and Institutional Research to ensure calculations, metrics, and institutional data definitions are consistently implemented across analytical deliverables and supports mentoring team members in using shared analytical assets.
Serves as a key technical resource for data science, predictive analytics, statistical modeling, and machine learning across the institution.
Evaluates complex business problems to identify where advanced statistical or machine-learning methods provide actionable value beyond traditional reporting.
Designs, develops, validates, and operationalizes predictive and analytical models aligned to institutional priorities including enrollment forecasting, student retention and completion, program alignment, financial optimization, and operational capacity planning.
Executes feature engineering, exploratory data analysis, regression, classification, clustering, and time-series forecasting, coordinating with Data Engineering and Application Engineering to integrate model outputs into enterprise platforms and workflows.
Evaluates and prototypes emerging capabilities in analytics, machine learning, and generative artificial intelligence to address institutional challenges and improve operational effectiveness.
Ensures data and analytics solutions comply with institutional data governance, security, privacy, and data-handling standards.
Collaborates with Data Governance to support data quality, lineage, metadata dictionaries, data classification, and responsible data usage.
Embeds responsible AI and data science principles across deliverables, including transparency, explainability, reproducibility, appropriate oversight, and documentation of data sources, transformations, calculations, and methodologies.
Engages with institutional stakeholders to convert complex operational needs into robust data and analytics solutions.
Partners across Data Engineering, Data Governance, Institutional Research, Application Engineering, and academic and administrative units to deliver integrated data products.
Communicates analytical findings, methodology, and technical concepts to technical and non-technical audiences.
Participates in technical design reviews, peer code reviews, and standard-setting initiatives, while monitoring developments in Microsoft Fabric, Power BI, and AI technologies.
Leads communications for projects, programs, or teams to maintain clarity, alignment, and transparency.
Demonstrates advanced mastery of required technical and functional competencies and takes ownership for delivering expected results.
Collaborates respectfully with colleagues, contributing to community and partnership, and translates priorities into actionable plans while managing time, resources, and dependencies.
Provides clear direction, support, and inspiration to team members while aligning work with organizational goals.

Requirements

Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field.
3 to 5 years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field.
Experience with Microsoft Power BI (or comparable BI technologies), including developing analytical data models and transforming source data into analytics-ready datasets.
Experience with data warehouses, lakehouses, data pipelines, or modern cloud-based data platforms with software development practices such as source control, testing, documentation, and code review.
Understanding of data visualization, dimensional modeling, business intelligence concepts, statistical analysis, and data science concepts.
Proficiency in Python (or a comparable programming language) used for data analysis, automation, or data science.
Strong SQL skills and experience working with complex analytical datasets.
Ability to translate business requirements and questions into data and analytical solutions.

Technologies

Microsoft Fabric, Power BI, SQL, Python, DAX, Power Query
OneLake, Lakehouse, Warehouse, Data Factory
Notebooks, pipelines, semantic models
Azure, scikit-learn, TensorFlow, PyTorch
Microsoft Purview
FERPA, CI/CD, DevOps, MLOps
Generative artificial intelligence

Preferred Qualifications

Master’s degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field.
5+ years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field.
Experience with Microsoft Fabric including OneLake, Lakehouse, Warehouse, Data Factory, notebooks, pipelines, or semantic models.
Experience with Power BI including semantic modeling, DAX, Power Query, performance optimization, and deployment practices.
Experience with Azure data and analytics services.
Experience developing predictive models or machine-learning solutions.
Knowledge of statistical modeling and forecasting, including regression, classification, clustering, and other advanced analytical techniques.
Experience with machine-learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar technologies.
Understanding of MLOps concepts including model versioning, deployment, monitoring, and lifecycle management.
Experience with Microsoft Purview or similar data governance and lineage technologies.
Experience with CI/CD or DevOps practices for data and analytics solutions.
Experience working with higher education, student, financial, workforce, or other complex institutional data.
Knowledge of data privacy, security, and regulatory requirements such as FERPA.
Relevant experience may be considered in lieu of formal education where appropriate, consistent with TSTC’s equivalency philosophy.

Skills & Abilities

Designs, develops, and maintains data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies, including data modeling, software engineering practices, and deployment management.
Develops Power BI dashboards, semantic models, and analytical products using DAX, Power Query, and Microsoft Fabric.
Applies data science, statistical modeling, machine learning, and predictive analytics to address institutional challenges and adapts to emerging tools and technologies.
Translates complex business requirements into scalable, reliable, and well-documented data and analytics solutions.
Applies data governance, data quality, privacy, security, and responsible AI practices to support trustworthy and compliant analytical solutions.
Communicates analytical findings and technical concepts clearly to technical and non-technical audiences.
Manages multiple assignments and priorities while maintaining accuracy, quality, and attention to detail, contributing to shared development practices, standards, code reviews, and continuous improvement.
Collaborates effectively across Data Engineering, Data Governance, Institutional Research, Application Engineering, and business stakeholder teams.
Demonstrates strong analytical, problem-solving, critical-thinking, and written and verbal communication skills.

Core Competencies

Communication: Leads communication efforts for projects, programs, or teams to ensure clarity, alignment, and transparency.
Job Knowledge & Job Performance: Demonstrates advanced knowledge and mastery of the technical and functional competencies required for the role.
Ownership & Accountability: Takes full ownership of assigned responsibilities and is accountable for delivering results that meet or exceed expectations.
Teamwork & Service: Collaborates effectively and respectfully with colleagues, welcoming different perspectives and fostering community and partnership.
Planning & Execution: Translates goals and priorities into actionable plans, managing time, resources, and dependencies to deliver results.
Critical Thinking & Judgement: Exercises independent judgment and applies critical thinking to evaluate options, balance risks, and make decisions that support both team and organizational success.
Leadership Without Authority: Leads by example, acting as a visible role model of the organization’s values, integrity, and high standards.

Employment Classification

This position is classified under the Fair Labor Standards Act (FLSA) as exempt and operates in a professional and instructional environment that may include campus offices, classrooms, or lab settings.

Reasonable Accommodations

TSTC will provide reasonable accommodations to qualified individuals with disabilities to enable them to perform the essential functions of the position.

Work Environment

The role may require movement across campus, participation in meetings, and engagement with faculty, staff, and students to support institutional goals.
Work is primarily performed in an office or academic environment using standard technology and communication tools.

Telework Eligibility

This position may be considered for telework options based on eligibility under TSTC’s Telework Policy, aligned with State of Texas requirements.

Availability and Communication Expectations

The employee must be reachable during assigned work hours through established communication channels as required by the role.

Travel Requirements

Periodic in-state travel to campuses or meetings beyond the employee’s designated or nearest base campus may be required based on business needs and will comply with TSTC and State of Texas requirements.

Confidentiality and Sensitive Information

This role requires attention to confidential and sensitive information appropriate to assigned responsibilities.

Employment Eligibility Verification

If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.
You will be required to present acceptable and original documents to prove identity and authorization to work in the United States.
Documents need to be presented no later than the third day of employment.
Failure to do so will result in loss of employment at TSTC.

Background Checks

A criminal history background check will be required for the finalist(s) under consideration for this position.

Location

Texas (onsite)

Minimum Experience and Education

Minimum experience: 3 years
Education: Bachelor’s degree

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8d ago

Senior Data Engineer

APPLY Arkansas

Arkansas

8d ago

Full time Backend Developer Marketing Senior

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Job Description

APPLY is building modern, cloud-based data foundations and looking for a Senior Data Engineer to help shape how data is modeled, governed, and activated across customer engagement platforms. You will work in an inclusive and safe environment while contributing to an engineering culture centered on delivery, upskilling, and practical, scalable data systems. The role is hybrid/remote-friendly, with flexibility for candidates based in Latin America.

What you’ll do

Collaborate with internal disciplines, vendors, clients, and stakeholders to define data requirements and the technology stack for projects.
Audit source systems such as CRM and marketing platforms (including Salesforce and Sailthru), then define migration guidelines covering what to migrate, target structure, and execution order for internal or third-party teams.
Translate business needs into technical specifications, including data streams, integrations, transformations, databases, and data warehouses.
Design and build dbt transformation layers on Snowflake, including identity resolution, a semantic layer, and consumption or reporting layers.
Build and maintain pipelines that activate data in customer engagement platforms such as Braze.
Run discovery audits of digital products (apps, games, web) and deliver data foundation recommendations.
Operate in git-based workflows with code review, dbt tests, and existing CI/CD processes for warehouse objects.
Define data architecture frameworks, standards, and principles for modeling, metadata, security, and reference data, and optimize for performance and cost.
Create a plan to populate new solutions with current and historical data.
Implement data security and access controls to support compliance with company policies and regulation.
Document sources, ELT/ETL processes, data dictionaries, and metadata to enable data discovery, including maintaining data lineage and data flow documentation.
Research and recommend new technologies, and develop best practices for data management, security, and privacy.

What you bring

Bachelor’s degree in Computer Science, Information Systems, or a related field.
At least 5 years of experience in data engineering or related fields.
Expert-level SQL and strong ELT/ETL experience with hands-on Snowflake usage.
Strong hands-on experience with dbt (modelling, tests, documentation, macros) and git-based workflows including branching, code review, and CI/CD.
Proven experience with data modelling (dimensional and semantic layers) and analysis techniques.
Experience with customer data modeling and identity resolution across CRM, marketing, and product sources.
Experience integrating data with customer engagement platforms such as Braze, Salesforce Marketing Cloud, Sailthru, or similar tools.
Experience planning data migrations, including source audits, mapping, target structure definition, and historical backfill.
Working knowledge of Python for data tooling and automation.
Working knowledge of at least one major cloud platform: AWS or GCP.
Ability to troubleshoot data issues and develop effective solutions.
Comfort producing written guidelines and recommendations for client and third-party teams.
Understanding of data privacy and security best practices.
Excellent communication and problem-solving skills, with fluent English.

Benefits and work setup

Agentic Delivery
Inclusive and safe environment
AI & Strategic Upskilling
Generous vacation policy
Flexible work arrangements

Location

APPLY is hybrid/remote-friendly. The preferred candidate should be based in Latin America, ideally working hours aligned to PT or ET. Candidates in Santiago, Chile can work out of the Santiago office as remote/hybrid employees. Candidates outside Santiago, Chile are fully remote employees. This role is listed for Arkansas (hybrid).

Technologies you may work with

Snowflake, dbt, ELT, ETL, SQL, git, CI/CD, Python, AWS, GCP, Salesforce, Sailthru, Braze, Salesforce Marketing Cloud, Spark/PySpark, Docker, Kubernetes

Nice to have

Snowflake (SnowPro) or dbt certification (cloud certifications welcome)
Spark/PySpark
Docker and Kubernetes
Experience with consumer or digital-product data (apps, games, subscriptions)

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8d ago

Data Engineer (SME)

Cintel Inc Huntsville, AL

Huntsville, AL

8d ago

Full time Analytics Big Data Data Analysis

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Job Description

As a Data Engineer (SME), you will support advanced intelligence and analytics initiatives at Redstone Arsenal in Huntsville, AL. The role focuses on delivering visual analytic applications and building or optimizing data analytics and enterprise database systems using structured and semi-structured data alongside open-source, COTS, and GOTS tools.

Responsibilities

Design, develop, and deliver advanced visual analytic applications for desktop and web-based platforms
Develop and implement data analytics solutions for bulk analysis of relational and semi-structured data
Apply advanced graphics, data visualization techniques, and high-performance computing to support intelligence workflows
Design strategies for enterprise database systems, including standards for operations, programming, and security
Design, construct, and maintain large-scale relational databases
Integrate new systems with existing data warehouse architectures
Optimize system performance, scalability, and functionality
Collaborate with cross-functional engineering and mission teams to ensure successful delivery of analytics solutions
Use open-source, COTS, and GOTS technologies to meet program and government requirements

Requirements

Active Top Secret (TS) security clearance
Bachelor’s degree (BS or BA) in Computer Science, Engineering, Information Systems, or a related technical field
Senior-level experience in data engineering, database design, and analytics development
Experience with: Java, AWS, ETL experience, Spark / Scala, SQL / PLSQL, Postgres, NiFi, Informatica, Linux, and data pipelines (development, optimization, and tuning)
Strong experience working with structured and semi-structured data sources
Experience designing and supporting enterprise-scale database and data warehouse systems
Proficiency with data visualization tools and analytic software for desktop and web environments
10+ years of related experience

Technologies

Java
AWS
Spark
Scala
SQL
PLSQL
Postgres
NiFi
Informatica
Linux

Preferred Qualifications

Experience supporting Department of Defense or Intelligence Community programs
Familiarity with high-performance computing environments
Experience integrating data analytics solutions into existing enterprise architectures

Work Location

Huntsville, AL (onsite)

Company Overview

Cintel Inc. is a Small Business providing strategies and services to support Government clients across Software Development, Operational/Tactical and Installation/Facilities Energy, Cyber Security, Modeling and Simulation, Data Science, and Programmatic support. Cintel delivers nimble, value-focused solutions with emphasis on people, connectivity, communication, and teamwork, based on the belief that people drive solutions by connecting people, information, teams, and experience to respond to customer needs.

Team Culture

At Cintel, Engineers, Analysts, and Developers are highly motivated, technical, and self-organized. The team places trust in members to develop technical solutions for ill-defined problems, including environments where requirements are lacking and solutions are not obvious. The organization also emphasizes self-motivation and learning new skills, supporting engineers who are eager to keep up with new technology trends and can work as strong problem solvers.

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8d ago

Cleared Data Engineer

Accenture Federal Services Washington, DC

Washington, DC

8d ago

$93k - $176k/yr Full time AWS Aws Data Warehouse Big Data

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Job Description

Accenture Federal Services is hiring a Cleared Data Engineer for an onsite role in Washington, DC. In this position, you will design, build, and maintain scalable end-to-end data pipelines and cloud-native data solutions that support analytics and reporting across teams, with the security clearance required for federal work.

What you’ll do

Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies.
Develop data processing and transformation workflows to support analytics and reporting needs.
Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets.
Collaborate with cross-functional teams including data science, analytics, and business units to deliver solutions aligned with business goals.
Implement validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability.
Support data governance, security, and automation initiatives within the data ecosystem.
Use AWS services such as S3, Glue, Lambda, and Redshift to build and deploy cloud-native data solutions.

What you bring

Experience with cloud-based ETL services (such as AWS Glue, Google Cloud Dataflow, or Azure Data Factory).
Experience with cloud data warehousing technologies (such as Amazon Redshift, Google BigQuery, or Snowflake).
Hands-on skills with Python, SQL, Spark, and PySpark.
Experience with data platforms including Databricks, Palantir, and Snowflake.
Familiarity with data orchestration and data quality processes.
Active Top Secret or TS/SCI or TS/SCI with polygraph clearance.

Tools and technologies you may use

Databricks, Spark, Python, SQL, PySpark
AWS (S3, Glue, Lambda, Redshift)
AWS Glue, Google Cloud Dataflow, Azure Data Factory
Google BigQuery, Snowflake, Palantir
Docker/Kubernetes, Hadoop/Spark, NiFi, ELK stack, ElasticSearch

Benefits

401(k)
Dental insurance
Parental leave

Bonus points if you have

Experience working with federal clients.
Experience with Docker/Kubernetes, Hadoop/Spark, NiFi, ELK stack.
Experience with Agile / Scrum.
Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi.
A data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer Associate, Google Professional Data Engineer, IBM Certified Data Engineer, or similar.

Pay range: USD 93,400 - 176,200 per year.

Work location: In person.

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8d ago

Lead Software Engineer - Data Engineer

JPMorganChase Houston, TX

Houston, TX

8d ago

Full time Backend Developer Manager Artificial Intelligence

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Job Description

The Lead Software Engineer - Data Engineer role sits within JPMorganChase Corporate Technology on an agile team building trusted, secure, stable, and scalable technology products. You will serve as a core technical contributor, leading development of production data pipelines and engineering practices, including enterprise-authorized AI-assisted engineering.

Responsibilities

Execute creative software solutions across design, development, and technical troubleshooting, applying approaches that go beyond routine thinking when breaking down complex technical problems.
Develop secure, high-quality production code and review and debug code written by other engineers.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes, including AI-assisted code review/refactoring, test strategy acceleration, and incident or root-cause analysis support.
Establish consistent validation standards across the team, including secure coding, peer review, and automated testing, and promote reuse of effective engineering patterns.
Apply knowledge of Software Development Life Cycle toolchain capabilities, including enterprise-authorized AI-assisted development and automation, to improve value realized through automation.
Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability of software applications and systems.
Lead evaluation sessions with external vendors, startups, and internal teams to probe architectural designs, technical credentials, and suitability for integration with existing systems and information architecture.

Requirements

Formal training or certification in software engineering concepts and 5+ years of applied experience.
Strong experience in Data Engineering using Python, SQL, and the AWS Tech Stack.
Strong hands-on Python/Java development experience, with the ability to design, build, and support production-grade applications and data pipelines.
Strong SQL skills and experience working with data processing and data engineering workloads.
Hands-on experience with AWS cloud services and building cloud-native solutions.
Strong experience with Databricks, including development and processing of large datasets.
Solid software engineering fundamentals, with experience delivering and supporting solutions in a production environment.
Demonstrated experience leading effective use of approved AI-assisted software development tools (for coding, code review, test acceleration, and troubleshooting), with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.

Technologies

Data Engineering
Python
SQL
AWS
Java
Databricks

Benefits

Comprehensive health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching and more

Preferred Qualifications, Capabilities, and Skills

Proficiency in automation and continuous delivery methods, with strong SDLC discipline including CI/CD, testing, code quality, and release controls.
Advanced understanding of agile delivery, application resiliency, and secure engineering practices.

About the Team

JPMorganChase Corporate Technology develops applications and provides technology support for corporate functions across the network. The role supports global teams serving Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and the Corporate Administrative Office, with alignment to evolving technology needs and technology controls agendas.