Top Data Engineering Manager Jobs

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

The Data Engineering Manager will oversee data engineers, develop data pipelines and ETL processes, and collaborate with cross-functional teams to enhance data architecture and strategy.

Lead a team of engineers in developing AI data platform services, focusing on system design, execution, and team culture. Oversee project outcomes and mentor team members.

The Platform Engineering Manager leads and mentors a team to build and manage an automated platform, ensuring reliability, scalability, and effective product management for internal services.

Manage the Data Lake engineering team at Apex Fintech Solutions, driving technical initiatives, collaborating with stakeholders, and ensuring scalable data solutions. Responsibilities include team leadership, Agile facilitation, technical strategy, risk management, and establishing best practices in data engineering.

Lead the enterprise data platform strategy and architecture, driving Snowflake/dbt-based platform evolution, self-service Data Mesh and medallion models. Build AI-ready pipelines, RAG systems, and observability/cost frameworks while managing a central data team, supporting federated BI, and executing hands-on technical work.

The Engineering Manager will lead the Data Platform team, overseeing data infrastructure and scalable systems, ensuring reliability and accessibility of data across products and teams, and driving technical vision and best practices.

Lead complex AI research initiatives in mental health, managing a team of data scientists and software engineers, while ensuring project goals and quality standards.

Lead the development of scalable data platforms and analytics systems, overseeing teams in building data pipelines, advanced algorithms, and dashboards for data-driven decision making.

The Senior Manager, Data Engineering oversees data engineering efforts, focusing on intelligent foundations and experiences. They are responsible for leading teams and optimizing data solutions.

Lead a global team of data scientists, data engineers, and ML professionals to deliver scalable analytics, automation, and AI solutions for pricing. Partner with business and IT to prioritize projects, ensure data quality and governance, drive Snowflake and AWS improvements, and communicate data-driven insights to senior stakeholders.

Lead and grow a data engineering team that designs, builds, tests, and operates large-scale data pipelines and warehouses. Partner cross-functionally to translate requirements, ensure data quality, observability, SLAs, security, and governance, and drive automation and performance for analytics, ML, and product use cases.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

As an Engineering Manager for Data Automation, you will lead a team to build and manage data processing systems using various technologies, ensuring high performance and reliability while optimizing workflows.

Lead and define a 1-3 year technical roadmap for a petabyte-scale realtime data platform. Modernize core data infrastructure, enable realtime analytics and AI-driven features, scale and structure engineering teams, hire and mentor managers and senior ICs, and partner with product and engineering teams to deliver governed, performant data and AI capabilities.

The Enterprise Data Engineering Manager will lead data implementations and architecture, establish frameworks, and mentor teams to deliver scalable data solutions.

The Data Engineering Lead oversees data engineering operations, manages teams, ensures data integrity, and drives innovation in data management and governance.

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

The Engineering Manager will lead the Data Visualizations Explorations team, set product direction, coach team members, and drive innovative data experiences for users.

Hands-on data engineering leader responsible for designing, building, deploying, and operating scalable data pipelines and platforms. Manages and mentors a team, provides architectural leadership across cloud-native and distributed data solutions, partners with stakeholders to translate business needs into reliable data products supporting analytics and AI/ML, and drives operational excellence and continuous improvement.

Manage and mentor the engineering team, set strategy and goals, collaborate with stakeholders, and evaluate technical trade-offs for ad data processing systems.

Lead a team of 4-10 data engineers to design, build, and maintain scalable ETL and data integration pipelines. Manage Agile delivery, enforce engineering best practices, optimize SQL performance, partner with analytics and product teams, drive automation, and ensure compliance with security and regulatory requirements.

Lead end-to-end delivery of data platform engagements: design and implement scalable ingestion and transformation pipelines, write and review production code (Python/SQL/Scala/Spark), architect cloud environments, advise clients, manage and mentor teams, and support practice development and business development activities.

Lead and mentor a data engineering team to design, build, and maintain data warehouse/lake architecture, ETL/reverse ETL pipelines, data models, performance tuning, monitoring, security, governance, and documentation while collaborating with stakeholders to support analytics, AI, reporting, and automation.

Lead and grow a Data Foundations engineering team building high-throughput, reliable data platforms. Drive architecture and delivery for ingestion, buffering, enrichment, replication, storage, and query layers (ClickHouse, CDC, event streaming), ensure operability across SaaS/Dedicated/Self-Managed/Cells deployments, hire and coach engineers, and collaborate cross-functionally to deliver customer-facing reporting and search capabilities.