Data Engineer Jobs in Bellevue, WA

Role focuses on ensuring data center security and resiliency, implementing controls and controls compliance, and protecting export-controlled information. The posting emphasizes eligibility to access export-controlled data and does not list specific technical duties or tools.

Build and maintain PySpark-based ETL pipelines and large-scale data workflows for finance. Write and optimize complex SQL, ensure data quality, collaborate with finance and engineering stakeholders, and document data models and processes to improve reliability and performance.

Lead design and implementation of multi-regional data platform and stream-processing architecture. Drive event-driven adoption, mentor engineers, ensure scalability, reliability, security, compliance, and participate in on-call operations.

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

Lead architecture and standards for CoreWeave's enterprise data ecosystem: design lakehouse/streamhouse architectures, modeling and semantic layers, governance, data quality, lineage, observability, and reusable data products. Drive cross-domain solutions, resolve performance and scalability constraints, evaluate core data technologies, conduct architecture reviews, and mentor senior engineers.

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.

Serve as first point of contact for customers using Agentforce and Data 360, troubleshoot technical issues, provide feature guidance and best practices, manage customer expectations, create and maintain knowledge content, participate in training, and escalate complex issues to internal teams to ensure customer success.

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.

Build and deploy production Data 360 implementations in enterprise customer environments. Develop ingestion pipelines, data models, identity resolution, retrieval systems, vector search, and AI-agent integrations. Write SQL and application code, test at scale, troubleshoot data and API issues, enforce security, and support production handoffs. Partner directly with customers, architects, developers, and implementation teams while documenting reusable scripts, tests, metadata, and runbooks.

Build and operate reliable, scalable, secure infrastructure for SaaS security and Snowflake data systems. Automate infrastructure provisioning, deployments, and incident response using Terraform, Spinnaker, Kubernetes, and related tools. Ensure security and compliance, participate in on-call rotations, lead incident response and root-cause analysis, and collaborate with development, data science, and security teams on architectural decisions and service implementation.

Design and implement data-intensive platform components, mentor engineers, and optimize streaming infrastructure to enable scalable data services at Okta.

The Software Engineer will manage data collection for model training, extend cloud infrastructure for ingestion pipeline, and collaborate with scientists to enhance data quality and efficiency.

As a Staff Software Engineer on the Storage Platform team, you will design distributed storage systems, improve database reliability and performance, build automation for database management, and ensure high availability for user-facing products.

Develop next-gen distributed data storage and processing systems, enhance query performance, and support diverse workloads from ETL to data science.

As a Staff Software Engineer at Databricks, you will develop distributed data storage and processing systems, focusing on projects like Apache Spark, Delta Lake, and performance optimization for diverse data workloads.

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.

Design, build, and operate large-scale offline data infrastructure and pipelines for ML training and experimentation. Improve reproducibility, observability, performance, and cost-efficiency across batch and streaming workloads while integrating orchestration systems and partnering with ML engineers.

Build and operate scalable data pipelines and feature datasets for ads ML. Own end-to-end offline flows from event ingestion to feature-ready datasets, develop batch and streaming systems, integrate feature store with online serving, improve observability and testing, and lead architectural decisions to ensure performance, correctness, and reliability at scale.

Early-career role to build, operate, and improve cloud data/analytics platforms (Fabric, Snowflake, Databricks). Support platform operations, CI/CD for analytics assets, onboarding for BI tools (Power BI/Tableau), runbooks, monitoring, incident response, and basic security/governance. Work under senior mentorship and contribute to automation, deployment templates, and performance triage.

Lead architecture, operation, and improvement of cloud data and analytics platforms (Fabric, Snowflake, Databricks). Own CI/CD for data assets, BI delivery (Power BI/Tableau), reliability, monitoring, incident response, security, and governance. Enable teams through standards, runbooks, and onboarding; troubleshoot performance and ensure production stability.