AWS

AWS Engineer Jobs

251 jobs found

Today

Data Engineer

Derex Technologies Inc Washington, DC

Washington, DC

Today

Full time Amazon Web Services AWS Aws Glue

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Job Description

Derex Technologies Inc offers a hybrid role based in the Washington, DC (DMV) area, with a primarily remote day-to-day and in-person client engagement when needed. You will build reliable analytics foundations and Power BI semantic models that help stakeholders make consistent, performance-focused decisions.

This position focuses on end-to-end ownership, from source ingestion and data quality to production dashboards, including governance, metric consistency, and an environment that supports both consumer reporting and self-service use.

What you’ll be responsible for

Build ingestion and transformation pipelines from operational systems, APIs, and files, including incremental loading, historization, and schema change handling.
Design analytics data models, including dimensional models, conformed dimensions, slowly changing dimensions, and aggregation strategy to improve query performance.
Implement data quality and reconciliation controls with alerting to surface issues before reports are impacted.
Orchestrate and monitor scheduled workloads with dependency management, retry behavior, and failure handling.
Develop Power BI semantic models, including DAX measures, relationships, row-level security, incremental refresh, and performance tuning.
Create reports and dashboards aligned to stakeholder questions, with attention to clarity, accessibility, and load time.
Administer the Power BI environment, including workspaces, deployment pipelines, gateways, capacity, and usage monitoring.
Define and document metric definitions so the same number represents the same meaning across datasets and reports.
Gather reporting and analytics requirements from business stakeholders and translate them into models, measures, and visuals.
Train and support report consumers and self-service users, and set guardrails to keep self-service dependable.
Document datasets, models, metric definitions, and lineage.
Contribute to solution design, estimation, and technical approach during presales and project planning.
Improve shared standards, reusable components, and report templates as new needs emerge from engagement work.

What you bring

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
Eight (8) years of professional data engineering or analytics engineering experience.
Proven experience delivering an end-to-end analytics solution from source ingestion through production reporting.
Significant Power BI experience, including semantic model design, DAX, and performance tuning (not report authoring alone).
Experience working directly with business stakeholders to define reporting requirements and metric definitions.
Experience supporting regulatory, compliance, or operational reporting where numbers are scrutinized is preferred.
Experience with public sector, SLED (state, local, and education), or higher-education clients is preferred, not required.
Must physically reside in the United States and be authorized to work in the United States.

Tools and technologies

SQL, Power BI, DAX, Power Query, M, Python
Azure Data Factory, Synapse, Databricks, Snowflake, AWS Glue
Git, CI/CD
Preferred Microsoft certification options: Power BI Data Analyst Associate, Azure Data Engineer Associate, or Fabric Analytics Engineer Associate

Additional details

Reports to: Engineering Lead
FLSA classification: Exempt
Location: DMV area, hybrid (primarily remote with in-person client engagement as needed)
Travel: Occasional travel within the DC-metro area for customer engagements and team on-sites
Background check required: Yes
Certifications: No certification required; Microsoft certification preferred

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Today

Data Engineers

University of Utah Health Salt Lake City, UT

Salt Lake City, UT

Today

$80k - $130k/yr Full time Amazon Web Services Analytics Apache Airflow

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Job Description

University of Utah Health’s University Analytics & Institutional Reporting (UAIR) office is seeking Data Engineers to design, build, test, implement, and maintain data transformation pipelines that support reporting and analytics. The role focuses on data modeling, automation, and advanced SQL work to enable reliable institutional insights.

Role Summary

In this hybrid position in Salt Lake City, UT, you will partner with teams to research source data structures and relationships, transform data into reporting-ready formats, and support analytics needs. Responsibilities include developing complex SQL queries, improving data quality through audits and correction processes, and maintaining documentation for data flows and processes.

Key Responsibilities

Research source data structures, relationships, content, and quality to support requirements discovery.
Design, build, implement, and maintain data transformation pipelines, processes, and reporting structures for data science, strategic reporting, master data sources, enterprise integrations, point-in-time snapshots, and related uses.
Automate and manage data quality audits and correction processes.
Write complex SQL queries to support analytics needs.
Develop and maintain data and process documentation, including data flow diagrams, data concepts, keys, definitions, and process steps.
Share ideas and knowledge, remain open to learning from others, and collaborate as new methods and tools are evaluated within continuous improvement.
Perform other duties as assigned.

Required Qualifications

Bachelor’s degree and 6 years of experience, or master’s degree and 4 years of work experience in institutional research, business analytics, data science, or a related field.
Proficiency in querying, manipulating, and analyzing complex datasets.
Excellent interpersonal and communication skills, including the ability to present complex data to technical and non-technical audiences.
Demonstrated experience with data visualization tools such as Tableau or Microsoft Power BI.
Experience with data querying languages such as SQL.
Proficiency in Python coding.
Experience working with APIs.
Demonstrated ability to manage multiple projects and work collaboratively across teams.
Equivalency statement: 1 year of higher education can be substituted for 1 year of directly related work experience (example: bachelor’s degree = 4 years of directly related work experience).

Preferred Qualifications

Advanced Oracle SQL skills to query and manipulate data and create and manage objects.
Experience and ability to move complex data transformation projects forward with minimal supervision.
6 or more years of experience in one or more of the following areas:
- Relational database or data warehouse programming/development, with an ability to translate business needs into sound technical solutions.
- Data reporting and analysis, including building queries from large relational databases for auditing data, ad hoc analysis, standard report generation, and an understanding of back-end reporting structures.
- Higher education administration with broad knowledge of student, faculty, HR, or finance data and processes, or experience managing data in an institutional research setting.
- Business systems analysis, including requirements analysis, data and process flows, liaising with functional and technical groups, testing, auditing data, troubleshooting, and issue resolution.
- Experience with PeopleSoft data, Tableau, Lucid Chart, and/or similar ERP systems, visualization, and diagramming tools.
- Experience building data pipelines in AWS using tools such as Glue and Apache Airflow.
A Master’s degree in MIS or a related field.

Technologies

SQL, Python, Tableau, Microsoft Power BI, APIs, Oracle SQL, PeopleSoft, Lucid Chart, AWS, Glue, Apache Airflow

Department Hiring Levels

Data Engineer, II: Requires a bachelor’s (or equivalency) + 4 years or a master’s (or equivalency) + 2 years of directly related work experience.
Data Engineer, III: Requires a bachelor’s (or equivalency) + 6 years or a master’s (or equivalency) + 4 years of directly related work experience.
Data Engineer, IV: Requires a bachelor’s (or equivalency) + 8 years or a master’s (or equivalency) + 6 years of directly related work experience.
Data Engineer, V: Requires a bachelor’s (or equivalency) + 10 years or a master’s (or equivalency) + 8 years of directly related work experience.

Compensation and Employment Type

Salary range: USD 80,000 - 130,000 per year
Experience requirement: 4+ years (minimum stated)
Education requirement: Master’s degree
Employment type: Benefited Staff

Benefits

Personal (401a) retirement account with employer contribution of 14.2%
Highly competitive health insurance
Generous paid leave time
Free public transportation pass (UTA)
50% tuition reduction for eligible employee and family members
Participating employer with Utah Retirement Systems (URS)

Additional Information

Hybrid work environment with a requirement to reside in the state of Utah and work from campus 3 days per week.
The office is not able to support individuals seeking sponsorship for visa; living and working from Utah is required.
Successful completion of a criminal background check and/or drug screen may be required.
The University values candidates with experience working in settings with students and a commitment to improving access to higher education.
Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law.
Reasonable accommodations are available in the application process for individuals with disabilities.
Online reports may be submitted at https://oeo.utah.edu
https://publicsafety.utah.edu/safetyreport/ provides statistics about criminal offenses, hate crimes, arrests and referrals for disciplinary action, and Violence Against Women Act offenses.
As per University of Utah policy 5-108, new hires who are still serving a 12 month probationary period will not be transferred into another University of Utah job until successful completion of probation.

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1d ago

Software Engineer

Wiliot Plano, TX

Plano, TX

1d ago

Full time Backend Developer API APIs

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Job Description

Wiliot is seeking a Software Engineer to design, build, and deploy data-driven applications that connect with Wiliot’s IoT cloud, device data, and enterprise systems. The position emphasizes backend services and microservices that process ambient IoT sensor data and support real-time supply chain insights.

Responsibilities

Develop applications and microservices using modern Python.
Design APIs and backend services to process and expose ambient IoT sensor data.
Work with data engineering and cloud platform teams to integrate real-time and batch data flows.
Participate in requirements gathering and product ideation.
Maintain scalability, security, and performance across software solutions.
Troubleshoot and resolve issues in production environments.
Write unit, integration, and end-to-end (E2E) tests to support code quality.
Contribute to CI/CD pipelines and DevOps processes.
Document technical decisions and support internal stakeholders.

Requirements

3–6 years of software development experience in backend or full stack roles.
Proficiency in Python.
Experience working with cloud platforms including AWS, Azure, or GCP.
Demonstrated experience with Apache Spark.
Familiarity with RESTful APIs, microservices, and event-driven architectures.
Solid understanding of relational and/or NoSQL databases such as PostgreSQL, MongoDB, or DynamoDB.
Comfort working in agile teams and fast-paced development environments.
Strong debugging, system design, and problem-solving skills.
Based in Dallas/NYC or willing to work hybrid in the Dallas/NYC office.

Technology Stack

Python, Apache Spark, AWS, Azure, GCP, RESTful APIs, microservices, event-driven architectures, PostgreSQL, MongoDB, DynamoDB, CI/CD, DevOps, unit tests, integration tests, E2E tests, CI/CD pipelines.

Preferred Qualifications

Experience with data-heavy applications, including IoT, telemetry, sensor networks, or analytics platforms.
Exposure to containerization tools such as Docker and Kubernetes.
Familiarity with Databricks.
Familiarity with edge/cloud integrations or device-cloud architectures.
Background in logistics, supply chain, cold chain, or RFID systems.

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1d ago

AI/ML Data Engineer

Swingtech Washington, DC

Washington, DC

1d ago

Full time Amazon Web Services Artificial Intelligence AWS

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Job Description

Swingtech is supporting the U.S. Department of Labor with AI/ML solutions that rely on reliable, secure, and well-governed data. As an AI/ML Data Engineer in a hybrid role based in Washington, DC, you will develop and sustain the data foundations that enable analytics, document intelligence, RAG, and production AI capabilities.

This position focuses on structured, semi-structured, and unstructured data pipelines, including document ingestion workflows, data modeling and governance controls, and operational support for secure training, validation, evaluation, and production datasets.

Responsibilities

Design, build, test, deploy, and maintain scalable data pipelines for batch, streaming, near-real-time, and event-driven workloads.
Integrate approved agency data sources, APIs, file stores, document repositories, relational databases, data lakes, data warehouses, and authorized external sources.
Develop ETL/ELT pipelines for extraction, validation, transformation, normalization, enrichment, de-identification, metadata management, and loading.
Implement document-ingestion pipelines supporting OCR, parsing, classification, metadata extraction, PII detection/redaction, chunking, embeddings, vector indexing, and retrieval workflows.
Create and maintain data models, schemas, data dictionaries, metadata structures, catalog records, and data-quality controls.
Implement data lineage, source provenance, dataset versioning, retention, access controls, and auditability across training, validation, evaluation, and production datasets.
Preserve separation of training, validation, and final evaluation datasets through controlled access, versioning, and documented lifecycle processes.
Develop and monitor data-quality measures including completeness, accuracy, timeliness, duplication, validity, freshness, distribution drift, and labeling quality.
Apply data minimization, masking, encryption, access controls, de-identification, and least-privilege safeguards for PII, CUI, and other protected DOL data.
Collaborate with AI/ML Engineers to improve retrieval quality, embeddings, vector stores, hybrid search, reranking, citation traceability, and knowledge-base refresh processes.
Develop data-pipeline runbooks, technical documentation, source inventories, lineage artifacts, data-quality reports, and operational support procedures.
Support security, privacy, ATO, Responsible AI, incident response, MLOps, monitoring, and release-readiness activities.

Requirements

Bachelor’s degree in computer science, data engineering, data science, information systems, software engineering, mathematics, or a related technical discipline.
At least 4 years of experience in data engineering, database development, analytics engineering, ETL/ELT development, data-platform implementation, or related work.
Strong SQL and Python development skills.
Experience designing data pipelines and integrating APIs, databases, file systems, cloud storage, data warehouses, or data lakes.
Experience with data modeling, metadata, data quality, data lineage, data transformation, monitoring, and operational support.
Familiarity with AWS, Azure, Google Cloud, or equivalent cloud data services.
Knowledge of secure data-handling practices, including access control, encryption, data masking, PII protection, and logging.
Willingness to work 3 days onsite at a customer site in Washington, DC.

Technologies

SQL, Python
AWS, Azure, Google Cloud
AWS Glue, S3, Athena, Redshift, Lake Formation
Azure Data Factory, Azure Data Lake Storage
Databricks, Snowflake, BigQuery
Vector databases: OpenSearch, pgvector, Pinecone, Weaviate, Milvus, Chroma, FAISS
RAG, OCR
Security and governance: FISMA, FedRAMP, NIST 800-53, NIST 800-171

Benefits

15 PTO days
11 paid holidays
Medical Insurance with 3 options (HSA with $600 employer contribution)
Dental Insurance with no age limit orthodonture
Vision Insurance through EyeMed in and out of network coverage
Short Term and Long-Term Disability coverage with 100% premium support
Life insurance and AD&D with 100% premium support
Supplemental Life Insurance
Critical Care and Accident Insurance availability
Pet Insurance through Nationwide
Employee Assistance Program
401k with enrollment from day one. 4% deferral by company
$1500 Annual Training Budget
$1500 Referral bonus
Eligibility for annual merit and discretionary bonus
Flexible work arrangements

Preferred Qualifications

Experience with AWS Glue, S3, Athena, Redshift, Lake Formation, Azure Data Factory, Azure Data Lake Storage, Databricks, Snowflake, BigQuery, or equivalent platforms.
Experience with vector databases or vector-search capabilities, including OpenSearch, pgvector, Pinecone, Weaviate, Milvus, Chroma, FAISS, or similar tools.
Experience with RAG, document intelligence, OCR, enterprise search, knowledge management, document classification, or content-ingestion pipelines.
Familiarity with Federal data governance, FedRAMP, FISMA, NIST 800-53, NIST 800-171, CUI, Privacy Act, and records-management requirements.

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1d ago

Data Engineer, WW Ops Finance - S&A

Amazon.com Services LLC Bellevue, WA

Bellevue, WA

1d ago

$132k - $179k/yr Full time Amazon Emr Amazon Web Services AWS

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Job Description

Amazon is building a unified data management and discovery platform for worldwide Finance teams, and needs a customer-focused Data Engineer to design, scale, and automate the underlying data infrastructure.

Responsibilities

Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and AWS services such as S3, Glue, Redshift, Lambda, EMR, and MWAA
Develop and optimize data models, metadata management frameworks, and catalog systems to support fast, reliable data discovery for thousands of internal customers
Build and maintain microservices and APIs (including API Gateway and Lambda) for platform capabilities like search, data ingestion, and cross-service integrations
Implement data quality frameworks with monitoring and alerting to support reliability, freshness, and governance and compliance expectations
Automate data onboarding workflows and self-service features to reduce manual work and shorten time-to-insight for data consumers and producers
Work cross-functionally with product managers, BI engineers, and business stakeholders to translate business needs into scalable solutions
Participate in system design, code reviews, and operational excellence practices including incident response, root cause analysis, and continuous improvement
Contribute to GenAI-powered features and AI-driven workflows that improve data discovery and analytics experiences

Requirements

3+ years of data engineering experience
1+ year developing and operating large-scale data structures for business intelligence analytics using OLAP technologies
1+ year developing and operating large-scale data structures for business intelligence analytics using SQL
1+ year developing and operating large-scale data structures for business intelligence analytics using Oracle
1+ year developing and operating large-scale data structures using ETL (Extract, Transform, Load) / ELT (Extract, Load, Transform) processes
Bachelor’s degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
Experience with data modeling, warehousing, and building ETL pipelines

Technologies

Python, SQL, ETL, ELT
AWS services: S3, Glue, Redshift, Lambda, EMR, MWAA
API Gateway
Oracle, OLAP technologies
DataZone, OpenSearch
Kinesis, FireHose, IAM roles and permissions
Non-relational databases / data stores: object storage, document or key-value stores, graph databases, column-family databases
Apache Spark, Elastic Map Reduce

Location

Bellevue, WA (onsite)

Compensation

USD 132,100 - 178,800 per year

Benefits

Health insurance (medical, dental, vision, prescription)
Basic Life & AD&D insurance and option for Supplemental life plans
EAP
Mental Health Support
Medical Advice Line
Flexible Spending Accounts
Adoption and Surrogacy Reimbursement coverage
401(k) matching
Paid time off
Parental leave

About the Team

Part of the Worldwide Operations Finance Standardization & Automation (S&A) organization, building a unified data management and discovery platform serving global Finance teams
Platform includes a dataset catalog, metric catalog, AI assistant, and interactive query experience for thousands of customers
Actively scaling to support 10+ domains and data producer teams
Technology includes AWS services such as DataZone, OpenSearch, API Gateway, Lambda, microservices architecture, and modern frontend frameworks

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1d ago

Data Engineer, Decision Intelligence Technology

Amazon Web Services, Inc. Bellevue, WA

Bellevue, WA

1d ago

$101k - $160k/yr Full time AWS Big Data Bigdata

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Job Description

AWS Kumo is building data platforms that help power customer-facing applications and support operations. In this onsite role in Bellevue, WA, you will develop and enhance the data foundation behind reporting and advanced analytics, with a focus on reliability, data quality, and scalable architecture. You will work closely with BI, data science, machine learning, business analysis, and product teams to deliver actionable insights and improve the support experience.

What you’ll do

Develop and improve data architecture, including data quality, monitoring, and data availability.
Collaborate with Data Scientists to implement advanced analytics algorithms that support statistical analysis, prediction, clustering, and machine learning using rich data sets.
Partner with Business Analysts to build and verify hypotheses that improve the AWS Support business.
Improve ongoing reporting and analysis processes to streamline self-service support for customers.
Stay current with big data technologies and run pilots to design data architecture that scales as customer experience data grows.

Requirements

1+ years of data engineering experience.
Experience with data modeling, warehousing, and building ETL pipelines.
Experience with one or more query languages, such as SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, or Scala.
Experience with one or more scripting languages, such as Python or KornShell.

Preferred qualifications

Experience with big data technologies including Hadoop, Hive, Spark, and EMR.
Experience with ETL tools such as Informatica, ODI, SSIS, BODI, or Datastage.

Technologies you may work with

SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala
Python, KornShell
Hadoop, Hive, Spark, EMR
Informatica, ODI, SSIS, BODI, Datastage
ETL

Compensation and benefits

Salary range: USD 101,300 - 160,000 per year.

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, and options for Supplemental life plans), EAP, mental health support, Medical Advice Line, Flexible Spending Accounts, and Adoption and Surrogacy Reimbursement coverage.
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

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1d ago

Data Engineer 5 - Enterprise Risk Management

Capital One McLean, VA

McLean, VA

1d ago

$230k - $262k/yr Full time AWS Azure Big Data

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Job Description

Capital One is hiring Data Engineers to help lead a cloud-first transformation for Enterprise Risk Management in McLean, VA.

Responsibilities

Partner with Agile teams to design, build, test, implement, and support full-stack development solutions
Provide technical influence across developers, data analysts, and data scientists with expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Develop using Python and Spark and work with open-source relational and NoSQL databases
Build and deliver cloud data solutions using platforms such as Databricks and Snowflake
Stay current on data engineering trends by experimenting with new technologies, contributing to technology communities, and mentoring others
Collaborate with product managers and software engineers to deliver robust cloud-first data solutions for large-scale customer impact
Independently design, build, and deliver cloud data applications with minimal support from supervisors or managers
Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reusability
Create scalable, resilient, and operationally efficient data pipelines and platforms that perform under increasing volumes and demands
Act as a force-multiplier through hands-on delivery, innovation, and skill growth for peers and junior engineers
Lead end-to-end, large-scale transformative data initiatives, including architecture decisions (for example, Snowflake vs Databricks) based on technical and business needs
Communicate technical concepts and data outcomes clearly to internal and external stakeholders

Requirements

Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
6+ years of experience in application development (internship experience does not apply)
4+ years experience in distributed data
4+ years experience with SQL
4+ years programming with at least one of: Python, Java, or Scala
4+ years designing and developing data pipelines
2+ years designing data models and end-to-end solutions using both relational and non-relational databases

Technologies

Python, Spark, SQL, Java, Scala, NoSQL
Databricks, Snowflake
AWS, Microsoft Azure, Google Cloud
EMR, Glue, Airflow, Dagster
Monte Carlo, Splunk
MongoDB, Cassandra, DynamoDB
Redshift

Benefits

Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
Comprehensive, competitive, inclusive health, financial, and other benefits supporting total well-being

Preferred Qualifications

Master’s Degree in Computer Science or related field
8+ years of experience in data engineering
4+ years of data modeling experience
9+ years of application development with demonstrated proficiency in Python, SQL, Scala, or Java
5+ years hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
5+ years experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
5+ years experience designing, implementing, and operating real-time or streaming data pipelines
3+ years of experience in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
5+ years working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
5+ years designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
3+ years working in an Agile development environment
3+ years developing user-centric reusable data products