Top Hybrid Data Engineering Jobs

Founding data engineer for an AI-focused incubator building 0->1 solutions: design and operate scalable ETL/ELT pipelines, ensure observability, work with BigQuery/Airflow/dbt/AWS Glue and varied databases, and contribute using Python and JS/TS in a seed-stage startup environment.

Design and maintain billing systems that transform patient engagement data into auditable invoice files. Reconcile clinical sources, codify billing logic in BigQuery/SQL, automate data cleanup with Python or Google Sheets scripting, identify and fix data gaps, and document workflows while partnering with Finance, Sales, Engineering, and Product to ensure reliable, scalable billing outputs.

Lead design and deliver cloud-based data engineering solutions across Agile teams. Build, test, and support full-stack data systems using big data, streaming, and cloud technologies; mentor engineers and ensure high-performance, well-tested code.

Lead and manage a data engineering team to design, build, test, and support cloud-based, full-stack data solutions. Collaborate with product and agile teams to deliver distributed, real-time, and batch data systems using big data and cloud technologies, mentor engineers, and ensure high-quality, performant code.

Lead the US Card data analytics team to build data products, drive adoption of Big Data and cloud (AWS) technologies, establish data governance, and support cross-functional decision-making through analytics, visualization, and strategic roadmaps.

Design and deploy GenAI-driven marketing analytics: build SQL pipelines, Python automation and FastAPI endpoints, develop attribution, RAG and multi-agent LLM solutions, fine-tune/evaluate models, and operationalize insights via cloud and visualization tools to improve marketing performance.

Early-career actuarial/data role supporting design and implementation of actuarial knowledge graphs and ontologies, data transformation/ingestion, modeling, validation, documentation, and collaboration with engineers and stakeholders to enable LLM-driven analytics and automation.

Early-career actuarial/data consultant who designs and implements structured data and ontological models, analyzes insurance datasets, supports data transformation and ingestion, contributes to modeling and automation, and partners with engineers and stakeholders to align actuarial requirements with technical solutions.

Lead enterprise-scale data architecture and end-to-end solution design for Cat Digital. Create interoperable data products, design system-to-system data flows and data models, evaluate and deploy data platform solutions, and collaborate with engineering and product teams to accelerate time-to-data-value.

The SOX Data Analytics & AI Manager will develop and implement data analytics and automation solutions for SOX compliance, lead a team, and collaborate across functions to enhance efficiency in internal controls.

This role involves designing data architecture and solutions, managing data pipelines, leading POCs, and collaborating across departments to implement data governance and quality practices.

Design and maintain scalable data pipelines, collaborate with cross-functional teams, manage data architectures, optimize Snowflake performance, and enhance data workflows.

Join Chewy as a Data Engineer I to learn and build ingestion and transformation pipelines, write SQL/Python for data prep, apply dbt Cloud modeling, monitor data quality, assist in triage, and collaborate with analytics and data science under senior mentorship while gaining exposure to Snowflake, Kafka, AWS, Terraform, and data observability.

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines; optimize SQL and database performance; translate business needs into data requirements; enforce best practices (version control, code reviews, validation); mentor junior engineers; deliver timely, robust data solutions for global clients.