Data Lineage

Data Lineage Engineer Jobs

6 jobs found

1mo ago

Senior Data Engineer

Matlen Silver Chandler, AZ

Chandler, AZ

1mo ago Closed

$60 - $65/hr Contract Senior Artificial Intelligence Data Engineer

This position is no longer accepting applications (closed Sep 17, 2026).

Job Description

Senior Data Engineer contract role in Chandler, AZ (Hybrid) supporting an ongoing enterprise program focused on AI-ready data and knowledge foundations.

Project: Project SPARTAN (ongoing), duration: 18 months
Location: Chandler, AZ (hybrid)
Work setup: 3 days onsite per week; Remote: not available
Employment type: W2 only
Compensation: USD 60-65 per hour

Responsibilities

Implement data management best practices across complex enterprise environments
Develop, govern, and improve structured and unstructured data and knowledge foundations for AI and agentic capabilities
Drive improvements across data foundation areas including:
- Data quality
- Governance
- Lineage
- Metadata
- Data modeling
- ETL and data pipelines
- Preparing data and knowledge assets for AI consumption
Partner with engineering, architecture, operations, governance teams, and subject matter experts

Requirements

Senior-level experience implementing data management best practices
Strong experience with MySQL and Oracle Database
Hands-on Python experience
Experience with ETL tools, specifically Informatica
Strong experience with SQL Server
Experience with Teradata
Strong understanding of data modeling and normalization
Experience developing and implementing data quality controls, validation, and remediation
Experience with data governance, metadata, lineage, ownership, and data freshness
Experience working with structured and unstructured data
Strong analytical and problem-solving skills
Ability to work cross-functionally with technical and business stakeholders

Technologies

MySQL
Oracle Database
Python
Informatica
SQL Server
Teradata

Benefits

Health, vision, and dental insurance (single and family coverage)
401(k) plan with employee contributions only

Desired Skills

Experience with Nateeza
Experience using AI tools
Knowledge of AI-ready data and knowledge management
Experience preparing data for AI, automation, search, or analytics
Understanding of AI grounding, context structuring, and metadata quality
Experience with network technologies or infrastructure environments
Experience creating reusable data standards, templates, controls, and documentation

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1mo ago

Sr Analytics Engineer

Northwestern Mutual Milwaukee, WI

Milwaukee, WI

1mo ago Closed

$119k - $178k/yr Full time Senior Analytics Artificial Intelligence

This position is no longer accepting applications (closed Sep 13, 2026).

Job Description

Northwestern Mutual is hiring a Sr Analytics Engineer in the Business Intelligence Center of Excellence to create reusable analytical assets and deliver trusted data products that support enterprise decision-making and AI-enabled insights. The role centers on metric certification, data lineage and metadata collection, data quality monitoring, and driving adoption of governed analytics across the organization.

Key Responsibilities

Own business and technical requirements for building reusable cross-domain analytical data products, with emphasis on metric certification, lineage identification, and metadata collection.
Partner with business stakeholders to define, document, and align metrics, KPIs, business rules, and analytical requirements to support consistency, trust, and enterprise reuse.
Build a scalable analytics layer that delivers consistent enterprise metrics (OKRs/KPIs), enabling self-service and trusted cross-functional business intelligence.
Define and maintain analytical data quality rules that connect technical standards to business requirements; proactively monitor and manage data drift.
Conduct routine data validation, reconciliation, and quality assessments across the analytics lifecycle and BICOE-supported products.
Drive cataloging of cross-domain analytical products for enterprise visibility and guidance on using assets in Atlan.
Promote adoption and reuse of analytical data products and other enterprise-approved assets.
Apply curiosity toward emerging technologies that improve data discoverability, contextual understanding, trusted analytical consumption, and AI-enabled decision support.
Collaborate with Data Solutions & Enablement and business stakeholders to ensure end-to-end alignment with enterprise data standards, governance practices, and approved data sources.
Establish a mentorship and coaching community within and beyond the BICOE.

Required Qualifications

Bachelor’s Degree in a related field.
5+ years in analytics, data, or technology-related roles, including 3+ years applying the listed technical skills in platforms such as Databricks, Snowflake, AWS, Atlan, etc.
Demonstrated understanding of Large Language Models (LLMs), including prompt engineering, model capabilities and limitations, and practical business applications.
Ability to translate ambiguous business concepts into structured metrics, analytical models, and reusable data products.
Proven capability to work cross-functionally with both business and technical stakeholders.
Experience with metric management platforms and strong collaboration skills in researching how metrics are sourced, calculated, and shared.
Strong aptitude for data quality, lineage, provenance, and governance in an analytics-focused environment.
Strong SQL skills, including query optimization and performance management.
Track record of collecting, designing, and maintaining large data models.
Experience developing large analytical datasets, semantic models, dimensional models, or curated analytical data products.
Strong understanding of modern data modeling principles, including data grain, dimensions, facts, hierarchies, and reusable business logic.

Technologies

Databricks
Snowflake
AWS
Atlan
Large Language Models (LLMs)
Prompt engineering
SQL

Skills Profile

Adaptive Communication (communicates complex service, product, system, or process details to targeted audiences and partners across technical and non-technical groups)
Business Application (translates business requirements and capabilities into technical solutions; aligns solutions to lines of business based on technology needs and business goals)
Cross Functional Partnering & Planning (coordinates collaboration across functions with different expertise)
Data Analytics (creates business knowledge through analysis and maintains data analysis data)
Data Integrity (resolves data issues to improve accuracy and consistency across the lifecycle)
Data Literacy (applies appropriate data for intended purposes; recognizes misrepresentation and escalates when needed)
Strategic Thinking (plans, designs, prioritizes, and executes high-impact initiatives)

Benefits

Flexible work schedules
Concierge service
Comprehensive benefits
Employee resource groups

Compensation

Annual salary range: USD 118,960 to 178,440.

Geographic Specific Pay Structure: Structure 110: USD 130,880.00 - 196,320.00
Geographic Specific Pay Structure: Structure 115: USD 136,800.00 - 205,200.00

Location and Work Model

Milwaukee, WI (hybrid)

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1mo ago

Principal Data Engineer, People Data

Okta Washington, DC

Washington, DC

1mo ago Closed

$197k - $271k/yr Full time Big Data Data Analysis Data Architecture

This position is no longer accepting applications (closed Sep 11, 2026).

Job Description

Okta is hiring a Principal Data Engineer, People Data (hybrid) to architect and deliver scalable data platforms that power candidate and employee lifecycle insights.

Responsibilities

Design, build, and continuously evolve high-scale data solutions to act as reference architecture and reduce friction for enterprise data access
Create data quality frameworks including monitoring, anomaly detection, and alerting, with governance, lineage tracking, and change management rigor for externally reported metrics
Drive consistent data modeling patterns, naming conventions, documentation standards, and metric governance across the data organization
Lead cross-functional technical initiatives across data verticals to accelerate delivery and harden data systems
Make sound technical decisions in ambiguous environments, balancing short-term execution with long-term infrastructure investment
Champion Data Contracts by implementing data contracts and schema evolution practices to support reliable outcomes across global product teams
Mentor and scale: mentor senior engineers, lead cross-functional task forces, and build a culture of engineering excellence and data-driven decision making
Stay current on data landscape developments, adopting and advocating emerging technologies and practices to shape the team’s long-term direction

Requirements

10+ years in data engineering with proven senior or lead experience
Federal government compliance and security requirements experience is highly desirable
Expert-level skills in SQL, ETL/ELT using Airflow and dbt, and MPP databases such as Snowflake and Redshift
Extensive hands-on experience with AWS services including S3, Lambda, EMR, ECR, and EKS
People Data expertise focused on HR data: candidate lifecycle, employee records, compensation, and organizational data
Experience designing data models for recruiting analytics, engagement signals, and workforce planning metrics
Familiarity with Workday data structures is a bonus
Experience building and maintaining batch and real-time pipelines using Spark and Kafka
Deep experience with modern lakehouse and warehouse architectures (including Databricks and Snowflake) and modern file formats such as Iceberg and Delta
Proven ability to integrate AI tools to optimize or redesign workflows with measurable impact (efficiency gains, quality improvements)
Track record of hands-on collaboration with Data Science, Business, and Product teams

Technologies

SQL
Airflow
dbt
Snowflake
Redshift
AWS (S3, Lambda, EMR, ECR, EKS)
Spark
Kafka
Databricks
Iceberg
Delta

Okta Experience

Supporting Your Well-Being
Driving Social Impact
Developing Talent and Fostering Connection + Community

Location: Washington, DC (hybrid) | Compensation: USD 197,000 - 270,600 per yearly | Minimum experience: 10 years

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1mo ago

Vice President, Data Products & Analytics Engineer

MUFG Jersey City, NJ

Jersey City, NJ

1mo ago Closed

$153k - $237k/yr Full time Analytics Atlassian Business Analytics

This position is no longer accepting applications (closed Aug 30, 2026).

Job Description

MUFG seeks a senior individual-contributor to lead data product strategy and execution within Data Management Engineering. Based in Jersey City, NJ on a hybrid schedule, the role shapes data product roadmaps and enables analytics, reporting, and AI-enabled data consumption across the enterprise. The position carries a salary range of USD 153,000 to 237,000 per year and requires at least seven years of data experience and a Bachelor's degree.

Responsibilities

Develop and sustain trust-based relationships with key stakeholders to understand business challenges and identify how data solutions can support objectives.
Empower business and corporate functions with robust data capabilities, ensuring clear lineage to products, services, and processes, while delivering valuable data insights and enabling seamless data access.
Optimize data product lifecycle management to modernize assets and maximize value, identifying process improvements to advance governance, management, and use.
Proactively engage data users to improve data maturity, promote adoption, and enable self-service, fostering a culture of continuous improvement and data systems thinking.
Partner with senior business stakeholders to understand strategic objectives and ensure data products support analytics, reporting, and data consumption needs.
Contribute to the technical and product direction for a portfolio of enterprise data products, translating complex business processes into curated, reusable, and governed data assets.
Provide expertise across the end-to-end data product lifecycle, including sourcing, design, engineering, quality, certification, and consumption readiness.
Translate business and analytics requirements into clear data engineering specifications and implementation plans, applying modern data architecture patterns for scalable data consumption.
Collaborate across engineering and analytics teams to promote common standards, tooling, and delivery practices within a matrixed environment.
Enable advanced data consumption capabilities, including BI, self-service analytics, and AI-assisted querying under governed access controls.
Contribute to data literacy and adoption by supporting documentation, data catalogs, and enablement of business data users.

Requirements

10+ years of data experience in the Banking and Financial Services sector from technology, data, or business operations perspectives.
10+ years of experience in data management and/or data product development.
7+ years of experience in business, systems, and data architecture and analysis.
Proven experience as a Data Engineer and/or Business Data Architect or similar role with a focus on delivering business value.
Bachelor’s degree in science, business, management, or finance-related fields.
Advanced degree is a plus.

Technologies

Snowflake
AWS-based data services
Collibra
Starburst
Informatica
Tableau
PowerBI
Alteryx
Relational databases and enterprise data warehouse technologies
Jira
Confluence

Benefits

Comprehensive health and wellness benefits
Retirement plans
Educational assistance and training programs
Income replacement for qualified employees with disabilities
Paid maternity and parental bonding leave
Paid vacation, sick days, and holidays

Data Products & Engineering Expertise

Demonstrated success modernizing data ecosystems through cloud-based platforms, automation, and integrated data solutions that improve data quality, accessibility, governance, and enable advanced analytics and AI-assisted data consumption.
Proven ability to design, scale, and operate modern data architectures including data marts, validation, and reconciliation frameworks to support end-to-end analytics and regulatory use cases.
Strong hands-on experience with cloud-based data platforms and modern data architectures.
Advanced SQL and substantial experience with data transformation, profiling, validation, and reconciliation workflows.
Practical understanding of AI-enabled data access patterns (semantic layers, natural language querying, curated retrieval) in regulated environments.
Solid grounding in metadata management, lineage, data quality controls, and certification workflows.
Experience in business, data, and application architecture and process re-engineering.

Leadership, Influence & Business Acumen

Expertise in business requirements analysis, design, and detailed design within the Banking & Financial Services sector.
Ability to operate with senior-level autonomy and influence across business, technology, and risk organizations.
Strong executive communication skills, capable of explaining complex technical concepts in clear business terms.
Detail-oriented while maintaining strategic perspective, with aptitude for storytelling and articulating a shared vision.
Effective at building alignment, driving adoption, and managing competing priorities in a matrixed organization.
Product-oriented mindset balancing near-term delivery, risk management, and long-term platform sustainability.
Proven ability to build consensus across multiple business areas to support new capability approaches.
Ability to adapt quickly as priorities evolve.

Technology & Tooling

Expert knowledge of tools and techniques spanning cloud platforms, programming languages, and modern software engineering practices.
Cloud data platforms such as Snowflake and AWS-based data services.
Enterprise data governance and metadata platforms such as Collibra.
Data virtualization platforms such as Starburst.
ETL tools such as Informatica.
BI and analytics tools such as Tableau, PowerBI, Alteryx or equivalents.
Relational databases and enterprise data warehouse technologies.
Agile delivery and collaboration tools including Jira and Confluence.

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1mo ago

Data Engineer II, AWS Analytics Engineering

Amazon Development Center U.S., Inc. Seattle, WA

Seattle, WA

1mo ago Closed

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

This position is no longer accepting applications (closed Aug 27, 2026).

Job Description

Benefits

Comprehensive health coverage including medical, dental, vision, prescription, plus Basic Life and AD&D with options for supplemental life plans
Support for mental health and access to an Employee Assistance Program
Medical advice line to help with clinical questions
Flexible Spending Accounts
Adoption and surrogacy reimbursement
401(k) plan with company matching
Paid time off and parental leave

Location: This position is onsite in Seattle, WA. Salary: USD 132,100 to 178,800 per year.

Responsibilities

Design, build, and operate the next generation ingestion service that automatically onboard data from any new AWS service or feature at launch, without manual work
Develop scalable ingestion frameworks capable of handling petabytes of data
Create and maintain big data procurement pipelines
Establish governance, compliance, and audit controls to ensure data integrity and security standards are met
Ensure the platform scales to support multiple services, supports event driven architectures, self-registration, and configuration driven onboarding with full lineage and audit trails
Build the foundational layer that enables all analytics capabilities within AWS Analytics Engineering

Requirements

5+ years of data engineering experience
3+ years designing and operating large-scale data structures for business intelligence analytics using ETL or ELT processes
3+ years developing and operating large-scale data structures for BI analytics with data modeling experience
3+ years of SQL experience
Experience with data modeling, data warehousing, and building ETL pipelines
Proficiency in at least one modern programming language (Python, Ruby, Golang, Java, C++, C#, Rust)
Experience with enterprise scale infrastructure or cloud programs/projects in a related industry
Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
Experience implementing data governance controls including access management, encryption, data classification, and audit logging

Technologies

Python, Ruby, Golang, Java, C++, C#, Rust
AWS Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, IAM, RDS

About the team

The AWS Analytics Engineering organization serves as the analytics backbone for AWS, powering decision making across more than 150 AWS services. The team processes petabytes of data daily through thousands of jobs, spanning transformations, reporting queries, ingestions, and infrastructure management scripts. You will join the Data Ingestion Platform team to design, build, and operate the next generation ingestion service that automatically onboard data from new AWS services at launch. The platform must scale with AWS service growth, support event driven architectures, and provide complete lineage and audit trails. The ideal candidate is a strong platform builder who thinks in terms of frameworks and abstractions, focused on laying the groundwork that enables all AAEs analytics capabilities.

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1mo ago

Data Engineer II

Amazon.com Services LLC Bellevue, WA

Bellevue, WA

1mo ago Closed

$132k - $179k/yr Full time Amazon Emr Analytics Artificial Intelligence

This position is no longer accepting applications (closed Aug 18, 2026).

Job Description

This Data Engineer II position at Amazon.com Services LLC is an onsite role based in Bellevue, WA. The role focuses on designing, building, and operating production SQL data pipelines within a cloud data warehouse, while contributing to a semantic layer to enable AI driven analytics at enterprise scale. The salary range is USD 132,100 to 178,800 per year, and the position requires a Bachelor’s degree or higher plus a minimum of three years of relevant experience.

Responsibilities

Develop, deploy, and maintain production grade SQL data pipelines within a cloud data warehouse
Define entity schemas, establish metric definitions, and own end-to-end data lineage from source to consumption
Deliver features across backend services and the frontend UI for the team's tools
Contribute to an expanding semantic layer that encodes business context for AI agents to consume
Collaborate with business stakeholders to translate operational knowledge into structured machine readable definitions
Own the operational health of what you build, including production alerts, on-call duties, ticket intake, access controls, and pipeline observability
Design, build, and operate production SQL pipelines processing large volumes of daily operational data from multiple upstream sources with strong reliability, freshness, and observability
Maintain end-to-end data lineage from raw sources through transformations to consumption to ensure downstream users and AI agents can trust numbers
Contribute to full-stack web applications used by business teams, shipping features across backend services and frontend UI to make data captureable, reviewable, and actionable at the source
Enhance the semantic layer with version controlled definitions of metrics, entities, relationships, and business context so operational knowledge resides in code and supports AI and LLM tools
Collaborate with stakeholders to translate domain expertise into structured, machine readable definitions and tables
Own operational health responsibilities including production alerts, on-call rotations, ticket intake, access controls (including row level security), and pipeline observability
Continuously seek opportunities to reduce manual analysis by moving toward natural language interfaces, richer entity relationships, and more autonomous investigation
Explore emerging techniques in semantic data modeling, knowledge representation, retrieval, and prompt engineering to improve how AI systems reason over data
Write design documents, scope documents, and runbooks to keep the team's work reviewable, maintainable, and durable

Requirements

3+ years of data engineering experience
Bachelor's degree or higher in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or related fields, or 3+ years of professional software development experience
Experience with one or more object oriented programming languages such as Java, C/C++, or Python
Background in data warehouse architectures, data modeling, infrastructure components, ETL/ELT and reporting/analytic tools and environments, data structures, and hands-on SQL coding
Experience with Redshift, Oracle, NoSQL databases

Technologies

SQL
Python
Java
C
C++
Redshift
Oracle
NoSQL
S3
AWS Glue
EMR
Kinesis
Firehose
Lambda
IAM

Benefits

Health insurance
401(k) matching
Paid time off
Parental leave

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