Top Hybrid Data Engineering Jobs

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.

Curate, cleanse, validate, and maintain large US equity and options datasets; integrate fundamental and alternative data; build data pipelines for research and trading; perform statistical and ML analysis to identify market patterns; document data provenance and collaborate with engineers and traders to deploy production-grade models.

The Knowledge Systems Architect will design systems for knowledge organization, automate documentation processes, and enhance knowledge artifact legibility to support AI effectiveness in the R&D environment.

Lead the design and implementation of enterprise-scale Knowledge Graphs and Semantic AI solutions, integrating graph intelligence and Generative AI. Manage cross-functional teams in data architecture and governance.

The Log Specialist at Dynatrace leads log management initiatives, collaborates with sales, architects data ingestion solutions, and advocates for enhanced log consumption strategies.

As a Senior Forward Deployed Accountant, you will architect and automate accounting processes, engage with CFOs, troubleshoot technical issues, and drive AI-driven transformation across enterprise accounts.

Lead and mentor engineering teams to design, build, test, and support cloud-based data platforms and streaming solutions. Implement big data, ETL, and data warehousing using cloud services and distributed tools, collaborate with product managers, and ensure high-quality, performant code.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

Lead design, build, and optimization of large-scale real-time and batch data ingestion and transformation pipelines. Integrate enterprise systems (SFDC, NetSuite, Workday), ensure data quality, observability, and reliability, and enable analytics/AI workflows. Architect solutions using Airflow, dbt, Python, Kafka, Snowflake, apply DevOps/CI-CD practices, mentor global teams, manage multiple projects, and align data engineering initiatives with product and business stakeholders.

Intern will build, test, deploy, and scale GTM data products and automation workflows using Python, Snowflake, GenAI/LLMs and BI tools. Partner with sales, marketing, renewals, and value teams to identify opportunities, drive adoption, and deliver self-service solutions. Contribute across project lifecycle from discovery to deployment.

Lead end-to-end analytics for unsecured lending collections: data discovery, translate business logic to technical specs, build and validate forecast models, automate risk signals, apply ML/NLP where appropriate, produce production-ready SQL/Python workflows, and communicate actionable recommendations to stakeholders.