Leads enterprise data engineering strategy, platform operations, architecture, modernization, and delivery. Oversees scalable pipelines, integrations, governance, data quality, observability, reliability, security, and cost efficiency. Manages engineering standards, backlogs, KPIs, production support, and multiple initiatives. Develops managers and technical staff while coordinating hybrid internal, contractor, vendor, and distributed teams. Partners with analytics, governance, security, infrastructure, and business stakeholders to deliver compliant, resilient data platforms.
Job Summary & Responsibilities
The Sr Manager, Data Engineering leads the delivery and operational excellence of enterprise data platforms, integration services, and engineering capabilities.
- Accountable for building scalable, secure, and reliable data foundations that enable analytics, governance, and business priorities across the organization
- Provides leadership across platform operations, engineering standards, delivery execution, and team development, while partnering closely with Analytics, Governance, Information Security, and business stakeholders to support compliance requirements, service
reliability, and operational efficiency
JOB FUNCTIONS
- Leads day-to-day execution and continuous improvement of enterprise data engineering capabilities and platform services
- Leads architecture and engineering decisions for scalable, secure, and resilient data platforms
- Drives modernization of data ecosystems through practical improvements to cloud and Lakehouse-based platforms
- Owns platform performance, reliability, cost efficiency, and service maturity
- Oversees delivery of enterprise data pipelines, integrations, and shared engineering services
- Ensures production-ready data assets and engineering solutions meet service, quality, and security expectations
- Establishes and enforces engineering standards, design patterns, and operational best practices
- Manages delivery planning, backlog prioritization, dependencies, and execution across multiple initiatives
- Defines enterprise standards for ingestion, transformation, orchestration, monitoring, and supportability
- Embeds governance, metadata, lineage, and data quality practices into engineering workflows
- Enables reusable frameworks, accelerators, and tooling that improves delivery consistency and scale
- Leads, mentors, and develops data engineering managers, technical leads, and individual contributors
- Drives performance management, succession planning, capability building, and career development
- Manages hybrid teams composed of internal employees, external partners, contractors, and offshore or nearshore resources to ensure coordinated delivery, accountability, and consistent operating practices
- Supports organizational design, hiring, and workforce planning to meet evolving platform and delivery needs
- Ensures data quality, control, and observability standards are embedded across pipelines and platform services
- Partners with governance, privacy, and security leaders to support regulatory compliance, audit readiness, and risk mitigation
- Champions engineering practices that protects sensitive data and supports enterprise governance objectives
- Partners with analytics, governance, security, infrastructure, and business leaders to align engineering priorities with enterprise needs
- Translates business demand into scalable engineering solutions, delivery plans, and operational priorities
- Defines and tracks engineering KPIs related to reliability, throughput, quality, service, and cost
- Drives continuous improvement across engineering processes, platform operations, and delivery performance
Education
- Bachelor's Degree in Computer Science, Information Systems, Engineering, Analytics, or a
related field; or equivalent combination of education and experience, Required
Work Experience
- Relevant leadership and technical background
- should demonstrate the ability to manage data engineering delivery, lead teams, and support reliable enterprise data platform operations
- 8--12 years of progressive data engineering, data integration, data platform delivery, or enterprise data architecture, Required
- 5--8 years of leadership managing data engineering teams, technical leads, or managers in a complex enterprise environment, Required
- managing hybrid delivery teams that include internal staff, external vendors, consultants, contractors, and distributed resources, Required
- Demonstrated background leading data engineering teams, establishing standards and operating practices, and supporting modernization of data platforms and integration capabilities, Required
- Strong expertise with SQL, ETL/ELT patterns, orchestration frameworks, and modern cloud or hybrid data platforms, Required
- leading delivery of scalable data pipelines, integrations, platform operations, and production support with a focus on reliability, performance, and cost efficiency, Required
- leading cloud or Lakehouse modernization initiatives using platforms such as Azure, AWS, Snowflake, Databricks, or Microsoft Fabric, Preferred
- working in regulated environments such as healthcare, finance, or other compliance-focused industries with strong governance and security requirements, Preferred
- partnering with analytics, governance, security, and business leaders to support platform priorities and enable enterprise data capabilities, Preferred
- Familiarity with Agile delivery models, product-oriented engineering practices, and DevOps or DataOps approaches, Preferred
Knowledge, Skills, and Abilities
- Strong expertise with SQL, ETL/ELT patterns, orchestration frameworks, and modern cloud or hybrid data platforms
- manage cross-functional priorities, resource planning, and stakeholder alignment across multiple initiatives and business partners
- Strong communication, executive presence, team development, and collaboration
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