Top Senior Data Engineer Jobs in Seattle, WA

The Senior Data Engineer handles ChowNow's data platform, collaborating with teams to enhance data availability and insights, supporting internal and customer-facing products.

Lead architecture and delivery of SoFi's data platform: build scalable data pipelines, drive cloud-native and AI-enabled tooling, enforce governance and security, mentor senior engineers, and support production on-call.

As a Senior Data Engineer, you will design and maintain data pipelines, define governance standards, and collaborate across teams to enhance Headway’s data architecture.

The Data Engineer designs and implements data solutions using AWS and Azure technologies, manages projects, interfaces with clients, and ensures documentation and testing for successful hand-offs.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Design, build, and validate pipelines to ingest, standardize, and publish real-world healthcare datasets (claims, EMR, registry). Perform SQL, Python, and SAS transformations, OMOP conversions, QA, and vendor communications to deliver high-quality datasets for analytics and research.

The Data Engineer at Netflix builds systems for efficient data processing and modeling, collaborating with various teams to empower analytical insights and product features.

The Principal Data Engineer will design and implement enterprise data frameworks, mentor teams, and ensure data quality while collaborating with stakeholders.

As a Staff Data Engineer, lead the technical roadmap for data infrastructure, manage complex data architectures, and mentor engineers while driving the organization's data platform innovations.

The Data Engineer will build scalable privacy-centric data frameworks, engineer data pipelines, and ensure compliance with privacy regulations at Netflix.

Lead design and implementation of scalable, HIPAA-compliant data pipelines and platforms for healthcare ML. Build ETL, orchestration, and tooling for processing EHR, claims, pharmacy, and bioinformatics data; collaborate with data scientists to produce modeling-ready datasets and ensure data quality, reliability, and operational excellence.

Lead and mentor a data engineering team to design and operate scalable ETL/ELT pipelines and Snowflake data warehouse solutions using Python, DBT, Matillion, and AI tools; establish standards, ensure data quality and governance, and collaborate with analytics, product, and BI stakeholders to deliver production-ready data platforms.

The Data Engineer will design, build, and maintain analytics-ready Data Marts, create resilient data pipelines, and ensure data integrity, working closely with analytics teams to deliver reliable datasets.

The Principal Data Engineer will lead the Data Resolution team, focusing on complex data challenges using Spark, system architecture, and mentorship, to optimize graph data pipelines.

The Data Engineer will analyze data, optimize systems, and collaborate with data scientists and engineers, requiring strong SQL and PowerBI skills.

The Data Engineer will design and maintain data models on Snowflake, enforce data standards, manage security, optimize SQL, implement CI/CD, and mentor junior staff.

The Staff Data Engineer designs and optimizes data platforms, leading projects and mentoring teams while ensuring data quality and performance across cloud environments.

The Lead Data Consultant will design and deliver scalable data solutions, manage project teams, and optimize client data environments, ensuring effective project execution and communication.

Lead design and implementation of a unified event-tracking data platform. Collaborate with Data, Product, and Engineering to build reusable event-publishing frameworks, monitoring/alerting, and deprecate legacy systems. Coach mid-level engineers, influence roadmap and processes, manage cloud/SaaS spend, create documentation, and participate in on-call rotations to ensure platform reliability and data trustworthiness.

Design, build, and optimize distributed query solutions using Starburst/Trino. Enable secure, governed data access across cloud and on-premises sources, implement data federation and query optimization, support IAM and governance in a federal environment, develop backend services and CI/CD, and troubleshoot performance in cloud-native systems.

Design and develop data solutions, maintain databases, enhance data quality, mentor junior engineers, and lead data process improvements.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

Design and maintain ELT pipelines, build dimensional (star/snowflake) analytics models, implement data transformations and quality checks, document data lineage and governance, partner with BI users, and mentor junior engineers to deliver performant analytics for business reporting and KPIs.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.

Design, implement, optimize, and maintain scalable, high-availability database solutions for a SaaS healthcare product. Integrate client data, resolve complex data issues, refactor systems for Azure, optimize MSSQL performance, participate in code reviews, and deliver features within Agile/Scrum to ensure reliable, high-performance data services.