Top Data Engineering Manager Jobs

Manage and grow the data engineering team while being hands-on with technical tasks, ensuring data quality and architecture improvements across platforms.

The Engineering Manager will oversee software solution design, lead engineering teams, manage performance, collaborate with Product Managers, and drive process improvements in a remote work culture.

Lead the Consumer Data Engineering Team, manage engineers, ensure alignment with business priorities, establish best practices, and deliver high-quality data products.

Lead the Data Platform team to develop data pipelines, manage engineers, refine processes, and actively contribute to architecture and code.

Lead the engineering team for Sift's data platform, manage data pipelines, establish processes, and contribute to architecture and features. Collaborate with product teams for strategy and growth.

Lead a team in developing scalable data solutions, mentor engineers, manage expectations, and contribute to code. Focus on high-quality software practices.

Lead and grow an engineering team building and porting safeguards offline data infrastructure across clouds. Own privacy-preserving data APIs and tooling for ML workflows, ensure compliance (e.g., HIPAA), manage incident response, coordinate cross-functionally with product and enterprise customers, and hire/mentor engineers while driving multi-cloud portability and zero-data-retention options.

Lead and scale a Solution Engineering team to translate complex enterprise data environments into outcome-driven AI strategies. Coach SEs on executive alignment, architecture narratives, deal orchestration, value-based selling, and risk management while balancing hands-on involvement with developing team independence and operational discipline.

Lead engineering for the Client Master Data Management (MDM) platform: translate product strategy into prioritized roadmaps, drive cross-functional alignment, own platform architecture and operational excellence, manage vendors and integrations, and ensure reliable, scalable data management solutions.

Lead and scale a Data & AI Support Engineering team to resolve complex Spark, streaming, Lakehouse, and Databricks issues. Build AI-enabled support workflows, automations, and runbooks; partner with Engineering/Product to operationalize diagnostics and observability; manage KPIs, escalations, hiring, training, and on-call incident response while acting as a technical escalation leader for enterprise customers.

Lead a cross-functional analytics engineering team to build real-time and batch pipelines, scale semantic modeling, ensure data governance, deliver customer-facing analytics products, deploy AI insights with guardrails, and hire and mentor engineers while owning end-to-end operational health.

The R&D Engineering Program Manager leads New Product Introduction programs, ensuring cross-functional alignment and successful product launches by managing risks and optimizing resources.

Lead a high-performing Data Visualization engineering team, manage technical debt, and implement processes that enhance product features and team productivity.

Lead and manage data engineering teams to design, build, and maintain high-quality data pipelines. Oversee automation, performance scripting, data modeling, database optimization, and quality-control processes. Collaborate with product, engineering, and operations to deliver data-driven features and support SEC-related data needs and AI/LLM integrations.

The Software Engineering Manager leads a team to design and maintain data processing systems and computational pipelines, collaborating across teams to support scientific research.

The Senior Manager will lead a team in Clinical Engineering and Data Analytics, focusing on AI-driven clinical outcomes and strategic direction for healthcare solutions in dental solutions.

Lead the strategy and execution for Calendly's data platform, overseeing engineering practices, team development, and cross-functional collaboration to leverage trusted data across the organization.

The Manager of Data Engineering will lead a team in optimizing data pipelines, manage complex projects, and ensure effective data solutions for the organization.