Top Hybrid Data Engineering Jobs

Design, build, and maintain scalable data pipelines and cloud data infrastructure. Ensure data quality, governance, and RBAC. Orchestrate batch ML pipelines, optimize performance and costs, collaborate with stakeholders, mentor team members, participate in on-call and incident management, and evaluate vendor/architecture tradeoffs.

Assist in developing and maintaining data pipelines and models, conduct data wrangling, and support dashboard creation. Ideal for university students eager to learn.

Lead design and engineering of an enterprise graph database platform for fraud and claims. Build graph data models, large-scale pipelines, optimize hybrid/cloud platforms, improve data governance, and consult cross-functionally to resolve high-risk data engineering challenges.

Design, build, and optimize OLAP/analytical data platforms, including dimensional models, materialized views, and semantic layers. Improve query performance and scalability, partner with ETL teams, support BI/observability/AI teams, implement data quality checks, and contribute to analytics standards and documentation.

Design, build, and operate scalable ETL/ELT pipelines ingesting data from APIs, queues, databases and files. Implement transformations, data quality, monitoring, and support batch and near-real-time use cases while collaborating with analytics and AI teams.

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.

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.

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.