Data Engineer Jobs in Bellevue, WA

The Principal GenAI Data Engineer will drive the design and implementation of scalable GenAI data platforms, focusing on robust data pipelines for structured and unstructured data. This role requires expertise in Python and AI data architecture, enhancing enterprise data capabilities.

The role involves designing and developing a distributed ML data platform for autonomous vehicles, collaborating with stakeholders, and mentoring engineers while ensuring operational excellence.

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.

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.

As a Staff Software Engineer, you'll design and operate scalable backend services, collaborate across teams, and ensure high system availability.

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 batch and streaming pipelines, own orchestration and warehouse loading, model data with dbt, define canonical metrics and semantic layer, ensure data quality/contracts and reliability, and ground LLM outputs in auditable healthcare data.

The Data Engineer will transform customer data into a unified ontology, manage data pipelines, ensure data quality, and support AI systems.

As a Senior Site Reliability Engineer, you'll ensure the reliability and performance of a Kubernetes-based data platform, focusing on scaling infrastructure, enhancing security, and optimizing deployment processes.

The Software Engineer will develop and manage data platforms for CoreWeave, focusing on performance, security, and scalability while facilitating data access and compliance with regulations.

Design and implement data platforms, manage data infrastructure, develop streaming architectures, improve performance, and ensure data compliance.

The Data Engineer builds scalable data pipelines and manages Azure resources, ensuring reliable data access and optimizing data models for analysis and reporting.

Design, build, and own the pursuit intelligence platform integrating GovWin IQ, SAM.gov, Salesforce, and D&B. Lead API integrations, ETL/ELT pipelines, account scoring/tiering engines, and data architecture. Provide technical leadership through code reviews, coaching, documentation, and standards to support business intelligence and Go/No-Go decisioning for Pursuit & Capture.

The Staff Data Engineer will lead the architectural design and implementation of a compliant data platform, collaborating with multiple teams to ensure scalability, reliability, and security.

Lead architecture and build control plane services for a petabyte-scale compute platform. Design multi-tenant resource management, intelligent scheduling, GPU and AI/ML workload orchestration, and Kubernetes operators. Drive integration with infrastructure teams, lead code reviews, set standards, and mentor engineers to deliver production-grade distributed systems.

Lead architecture and implementation of enterprise-scale AI, software, and data platforms for network data. Build cloud-native, distributed systems and reusable AI services (Generative AI, RAG, Agentic AI). Provide technical leadership, evaluate emerging technologies, produce architecture designs, mentor engineers, and remain hands-on contributing to design, implementation, and code reviews to deliver scalable, secure, and highly available AI-powered solutions.

Design and build scalable, secure infrastructure and core clean-room features for multi-party data collaboration. Implement developer APIs, AI-enabled capabilities and agents, partner with product and cross-functional teams to deliver production systems, and mentor peers to ensure technical excellence and privacy-preserving analytics.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

Lead the architecture of core data processing systems for Snowflake, focusing on distributed systems and high-performance data transformation, ensuring efficiency and reliability at scale.

The Software Engineer will manage data collection, enhance cloud infrastructure for ingestion, and collaborate with scientists on AI data projects to support model training operations.

The role involves data collection for model training, building datasets on GCP, and collaborating with AI scientists to enhance data processing workflows.

As a Senior Data Engineer at Auger, you will build data systems to transform customer data into a unified ontology for analytics and AI workflows, ensuring data quality and managing the data lifecycle.