Top Data Engineering Manager Jobs

Hands-on technical manager who leads a small development and data engineering team to design, build, and deliver software, data pipelines, integrations, and BI solutions. Oversees CRM/platform development, API integrations, data warehousing, reporting, release management, and compliance/data governance while contributing to architecture and coding.

The Manager of Data Engineering leads a team to implement data architecture, manages project execution, and ensures pipeline quality. Responsibilities include team management, setting standards, developing engineering culture, and collaborating with stakeholders.

Lead Applied Data Engineering at HackerOne, developing high-performance data products and fostering collaboration while driving innovation and continuous evolution.

Lead a team of engineers in developing offline perception algorithms and data mining tools to produce high-quality data for autonomous driving.

The Manager of Data Engineering will oversee data engineering for an investment management firm, focusing on MS Fabric, Azure, and various data processing tasks.

Manage a team developing accelerated image and data compression libraries. Define project goals, roadmap, and scope; ensure execution and delivery; elevate engineering practices; collaborate with internal and external customers and the open-source community while fostering an inclusive, innovative environment.

Lead and develop a data engineering team to design, build, and operate Databricks-based, medallion-architecture data pipelines. Ensure platform reliability, performance, observability, data quality, governance, and support cloud migration efforts while partnering with cloud, architecture, and governance stakeholders.

Lead design and implementation of enterprise integration and data engineering. Manage integration capabilities, establish data governance, and ensure compliance and quality of data flows across applications.

Lead the strategy and governance of the data platform, ensuring its stability and adoption for impactful analytics. Oversee team management, platform architecture, and operations while fostering collaboration across business stakeholders and technical teams.

Lead cross-functional initiatives on data analytics related to user behavior, support legacy application replacement, and manage stakeholder coordination and project timelines.

Lead a team of data scientists to develop LTK's AI platform, manage performance, and drive execution of machine learning projects to enhance user experiences.

Lead product management for Lakeflow, impacting data engineering across Databricks' product portfolio. Manage the full product life cycle and collaborate with technical teams.

Lead and evolve the Claims Data Platform by managing database operations and architecting scalable, event-driven data pipelines. Build APIs and self-service data products, implement data quality and governance, partner with analytics and compliance teams, and report platform health and roadmap progress to leadership.

The Engineering Manager will lead a team of software engineers, collaborating with data scientists and geologists to build robust data systems for mineral exploration. Responsibilities include planning and prioritizing projects, coaching team members, and contributing as an individual on critical tasks.

This role involves leading the Data & AI team, building modern data platforms using Microsoft technologies, overseeing project delivery, and mentoring team members while engaging with clients.

Lead the architecture and delivery of enterprise data platforms, optimize data pipelines, enable AI/ML use cases, engage clients on technical strategy, and develop the data platform team.

The Manager for Data Engineering will lead the Data & AI team, focusing on building modern data platforms, providing mentorship, and overseeing project delivery using Microsoft technologies.

The role involves leading data engineering and analytics teams, optimizing data systems, collaborating on data pipelines, and managing data infrastructure projects.

Lead and develop data engineering leadership and teams to deliver scalable enterprise data products and platforms. Own product lifecycle, roadmap, and execution; design scalable pipelines and frameworks; enforce data quality, governance, and observability; partner with stakeholders to align data strategy to business outcomes; evaluate and implement modern data technologies; drive adoption and reliability across domains.

Lead and grow a full‑stack engineering team building customer data and identity solutions. Own architecture, APIs, component libraries, code quality, hiring, mentoring, roadmap execution, and cross‑functional collaboration. Contribute code for high‑impact items and ensure scalable systems and agile best practices.

Lead and mentor a data engineering team to deliver cloud-based data warehouse solutions. Drive architecture, code quality, CI/CD, source control, security, governance (SOX), and vendor coordination while implementing Snowflake, dbt, Matillion, Oracle, and SQL Server-based ELT/ETL pipelines.

Lead a data engineering team to develop and maintain data warehousing solutions, manage legacy integrations, guide architecture and vendor partners, deliver projects using Agile, monitor data quality and platform health, and engage stakeholders to align technical work with business needs.

The Engineering Manager will lead a team of data engineers, manage architectural decisions, and ensure platform reliability and scalability while collaborating on the data infrastructure roadmap.

Lead Data Acquisition Team, drive AI-augmented development, establish specification-driven methodology, oversee data pipeline architecture and ensure operational excellence.

Lead a team to design, build, and govern an enterprise Finance Data Repository (FDR). Responsibilities include data architecture, pipeline engineering, semantic layer and feature-store design, AI/ML enablement (RAG, embeddings, anomaly detection, NLQ), integration with BI and treasury systems, regulatory-grade lineage and controls, stakeholder engagement, and team development.