Top Data Engineer Jobs

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

Architect and scale cloud data platforms and ETL/ELT pipelines (batch and near-real-time), ensure data quality and observability, implement CI/CD for data infrastructure, collaborate with stakeholders and mentor junior engineers to deliver analytics and machine-learning-ready data products.

Ensure timely, high-quality data conversions from legacy systems to new platforms. Work with Implementation Specialists and Project Managers to execute conversion tasks, validate data integrity, troubleshoot issues, support deployments, and assist scheduling and customer communications.

Design, build, and own robust batch and real-time data pipelines and golden datasets using SQL and Python. Ensure data quality, performance, schema design, and SLAs while partnering across engineering, product, and business teams. Advocate tooling and best practices, document datasets, and deliver reliable analytics infrastructure at petabyte scale.

Lead architecture, strategy, and hands-on execution for Faire's data platform. Build and scale secure, cost-efficient data ingestion, ETL/ELT, warehousing, orchestration, monitoring, and governance. Mentor engineers, influence cross-team priorities, and drive performance and cost optimization for analytics and data products.

Lead design and implementation of scalable batch and streaming data infrastructure. Build and maintain ETL/ELT pipelines, ensure data quality and observability, troubleshoot production issues, mentor engineers, and partner with cross-functional teams to deliver reliable, self-serve data products.

The Senior Data Engineer will architect and scale data infrastructure, focusing on HRIS, Market Research, and Revenue Cycle pipelines, manage data products using Dagster, and oversee data governance while mentoring junior engineers.

The Senior Data Engineer will design and optimize data infrastructures and pipelines, lead projects, mentor juniors, and enforce best practices.

As a Senior Data Engineer, you will design, build, and scale data pipelines and analytics capabilities, focusing on data modeling, ingestion, and automation using Python and PySpark in a healthcare context.

Lead design and implementation of scalable ETL/ELT pipelines and Snowflake data models. Optimize workflows, ensure data quality and observability, support BI (Tableau, Domo, Power BI), mentor engineers, and drive data platform architecture and roadmap.

Founding technical leader for the data platform: build and operate ingestion, enrichment, batch and realtime pipelines; design storage, modeling, and governance; integrate LLM/ML workflows and vector search; hire and lead a small data team; and collaborate with engineering, product, and leadership to productionize data for valuations, analytics, and APIs.

Design, build, and operate a scalable, resilient Data Lakehouse. Lead architecture, evaluate open-source tooling, ensure performance and usability, mentor engineers, collaborate across teams, and drive DevOps and cloud best practices.

The Senior Data Engineer will design and implement complex data models, collaborate on data governance, lead data initiatives, and mentor team members.

The Sr. Data Engineer will design and maintain data pipelines, enhance data reliability, and collaborate with trading strategists to improve platform capabilities.

Own and evolve the data platform by leading architectural evolution, collaborating with teams for strategic data initiatives, and ensuring reliable data systems.

Lead design and delivery of scalable data integration, storage, and infrastructure to enable analytics and AI. Build ETL/ELT pipelines, cloud-native data systems, IaC and CI/CD, ensure SRE practices (SLOs/SLIs), prototype end-to-end solutions, and drive architectural trade-offs while collaborating across teams to transition validated solutions to platform engineering.

Design, develop, and maintain AxiomSL data sources, mappings, and regulatory reports. Build scalable data pipelines, perform advanced SQL transformations, ensure data lineage and reconciliation, support audits and production L2/L3 operations, and drive automation and platform upgrades to meet regulatory requirements.