Top Data Engineer Jobs

Design enterprise-grade data solutions using Databricks and Azure, optimize data pipelines, ensure compliance, and lead integration architecture efforts.

Develop and maintain data pipelines and reporting tools, support real-time processing workflows, and collaborate with teams to enhance platform capabilities, utilizing Java, Python, and Groovy scripts.

The Data Migration Engineer will design and execute SQL-based ETL processes for migrating public safety data, ensuring high-quality data integration and collaboration with internal and external teams.

As a Senior Data Analytics Engineer at Envoy, you will develop the Intelligence Platform, guide product strategy, support ML workflows, and ensure engineering rigor while mentoring team members.

The Senior Data Engineer Contractor will design and implement ETLs in Databricks, modernize data pipelines using Python and SQL, and ensure data governance and quality standards.

The Senior Data Engineer will build and maintain ETL pipelines, enhance entity resolution processes, implement risk calculation logic, and collaborate with product and development teams to refine requirements and manage data releases.

The Data Analytics Platform Engineer will design, build, and maintain data pipelines and scalable platforms, leveraging technologies to derive insights from gathered data for various mission-driven projects.

As a Data Analytics Platform Engineer, you'll design data pipelines, manage analytics platforms, and leverage technologies for impactful data solutions across various missions in cybersecurity and data analysis.

As a Senior Data Engineer I, you will build data capabilities for product expansion, integrate external APIs, design robust data pipelines, and collaborate with various teams to enhance systems and practices.

The Data Analytics Engineer will build reliable data pipelines, transform data for analysis, and create dashboards and reports while collaborating with cross-functional teams.

Lead design and implementation of batch and streaming data pipelines, build data models, implement data quality and testing, manage orchestration and IaC, mentor engineers, and communicate technical direction and tradeoffs to stakeholders.