Top Data Engineer Jobs in Seattle, WA

Design, build, and support complex batch and streaming data pipelines from structured and unstructured sources. Collaborate with engineering and analytics to deliver accurate, performant data, automate processes, maintain dev/test/prod environments, and participate in on-call rotation.

As a Data Engineer, you will design, implement, and maintain data systems for Notifications at Whatnot, ensuring data quality and performance while collaborating with cross-functional teams on data architecture and workflows.

Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.

Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.

Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.

Design, build, and maintain enterprise data warehouse and data lake solutions. Develop, tune, and operate ETL pipelines and SQL for analytics. Own end-to-end features, collaborate with analytics and engineering teams, and evolve data storage and ingestion platforms.

Serve as chief architect for a unified, Snowflake-managed Apache Iceberg Data Lakehouse on AWS. Design scalable ingestion (batch/stream), multi-tenant data mesh and RBAC, semantic layer for BI/AI, standardize medallion ELT (dbt, PySpark, Snowpark), automate with Terraform, mentor senior engineers, and drive cross-org integration and stability.

Build and operate production data pipelines integrating ERP/ATS/project management/telemetry into a queryable layer. Own the data model for a live knowledge graph. Ship SLA-backed datasets/services for tools and ML. Convert unstructured vendor/field data (PDFs, spreadsheets) into trusted structured inputs. Ensure data quality via tests, monitoring, and lineage, and use modern data stacks and LLM tools responsibly.

Lead architecture, build, and maintain scalable people-data platforms and pipelines. Establish data quality frameworks, governance, lineage, and data contracts. Drive consistent modeling, monitoring, and schema evolution. Lead cross-functional initiatives, mentor engineers, and collaborate with analytics, data science, and HR to enable recruiting, workforce planning, and employee lifecycle insights. Advocate emerging data technologies and integrate AI to improve workflows and impact.

Architect and build high-scale product telemetry and lakehouse data solutions. Lead cross-functional initiatives, implement data contracts, enforce data quality, lineage, governance, and mentor senior engineers to drive reliable, scalable product analytics.

As an Analytics Engineer, you will create scalable solutions for data reporting, build data pipelines, and establish high data integrity standards while collaborating with multiple teams.

Lead architecture and implementation of end-to-end data and analytics platforms for CoreAI. Design and optimize large-scale ETL/ELT pipelines, ensure data governance, quality, lineage, security, and enable self-service analytics. Collaborate with product, engineering, AI research, and business stakeholders to translate needs into roadmaps and data solutions. Mentor senior engineers and drive engineering standards, operational rigor, and scalable analytics for AI workloads.

Operate and evolve AMP platform to ensure reliability, security, compliance, cost efficiency, and operational excellence. Monitor health and capacity, manage incidents and escalations, provision Azure/Fabric resources, enable onboarding, drive security and compliance remediation, optimize costs and capacity, coordinate with product groups and vendors, and improve automation, observability, and operational tooling.

Design and build foundational dimensional data models, enterprise metrics, and curated data products on a modern lakehouse. Partner with business domains to translate processes into scalable, high-quality datasets, optimize analytical workloads, and operate distributed processing systems to support analytics, BI, and AI.

Build, model, and maintain scalable BigQuery-based data solutions on GCP. Implement performant data models, storage partitioning/clustering, ETL improvements, data validation, and documentation. Collaborate with architects, data scientists, and engineers to deliver governed, high-quality data for reporting and AI initiatives.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.

Build and maintain governed Silver/Gold data models and semantic assets on Databricks. Translate stakeholder KPIs into testable, reusable transformations, apply enterprise modeling standards, enable domain self-service, ensure data sensitivity and governance, and review domain-contributed models for production readiness.

Own and evolve the data lake and analytics stack powering fleet observability. Build and maintain scalable ETL/ELT pipelines, operate data lake infrastructure (Iceberg, Trino, Airflow, Spark, Superset), produce analytics and executive reporting, create dashboards and runbooks, and implement data governance and observability.

Design, develop, and optimize Teradata data solutions: elicit requirements, create logical/physical designs, write SQL (views/procs/macros), use Teradata utilities for data loads, tune performance for large datasets, coordinate stakeholders, and write Unix shell scripts.

Elicit and analyze requirements; design logical/physical Teradata solutions; develop ETL using Teradata utilities; write SQL (views, stored procedures, macros, functions); perform performance tuning for large datasets; write Unix shell scripts; coordinate with stakeholders and support BI/DW initiatives.

Build and maintain data infrastructure to measure agent behavior and user interactions, design evaluation frameworks for AI agents, analyze user behavior to inform product strategy, and partner with engineering and leadership to solve high-impact business problems using data.

Design, build, and operate scalable cloud data pipelines and ELT/ETL processes (batch and streaming) into Snowflake. Automate monitoring, triage incidents, optimize performance and costs, enforce access controls, and provide on-call support. Collaborate with Product, Platform, and Architecture teams, document runbooks, and mentor junior engineers while researching emerging tech and improving observability and CI/CD for data deployments.

Lead architecture and evolution of Headway's data platform (warehouse, ingestion, orchestration, CI/CD, monitoring, cloud infra). Serve as technical anchor across analytics, product, and ML teams, drive platform roadmaps, set standards, mentor engineers, and own end-to-end infrastructure decisions for scale and performance.

Build, deploy, and operate production-grade data pipelines and data products for healthcare audiences. Design transformations, data models, and governed views using Python, SQL, Airflow, S3, Snowflake, and EMR. Implement data-quality, monitoring, and privacy-by-design controls for PHI/PII. Partner with product, analytics, and platform teams to onboard sources, support audience discovery, segmentation, activation, measurement, and troubleshoot production issues.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.