Technical Project Manager - Data Engineering

Job Summary

We are seeking an experienced Project Manager - Data Engineering to lead the delivery, governance, and operational management of enterprise data platforms and analytics initiatives. The role is responsible for managing a team of data engineers, driving project execution, ensuring adherence to architecture and engineering standards, and delivering business value through scalable and reliable data solutions.

Responsibilities

• Delivery Management
  • Own end-to-end delivery of data engineering, analytics, and platform modernization initiatives.
  • Manage project scope, timelines, budgets, risks, dependencies, and resource allocation.
  • Establish delivery governance and ensure projects meet quality, schedule, and business objectives.
  • Drive delivery planning, status reporting, issue resolution, and executive communication.
• Team Leadership People Management
  • Lead, mentor, and develop a team of Data Engineers and Technical Leads.
  • Drive workforce planning, onboarding, capability development, and succession planning.
  • Establish performance expectations and promote engineering excellence.
  • Foster a culture of accountability, collaboration, continuous improvement, and innovation.
• Data Platform Engineering Governance
  • Govern the implementation and support of enterprise data platforms, data lakes, Lakehouse architectures, and analytics solutions.
  • Ensure adherence to architecture standards, security policies, development guidelines, and operational processes.
  • Lead architecture and design review processes to ensure solution quality and compliance.
  • Drive standardization, reuse, automation, and operational efficiency across the data ecosystem.
• Stakeholder Business Engagement
  • Partner with business leaders, product owners, enterprise architects, and technology teams to define priorities and delivery roadmaps.
  • Translate business objectives into executable delivery plans.
  • Manage stakeholder expectations and ensure alignment between business outcomes and technical solutions.
  • Provide regular updates to leadership on delivery status, risks, and strategic initiatives.
• Data Quality, Compliance Risk Management
  • Ensure implementation of data governance, security, privacy, and compliance requirements.
  • Establish controls for data quality, monitoring, and operational readiness.
  • Identify delivery risks and implement mitigation plans proactively.
• Analytics AI Enablement
  • Enable enterprise reporting and analytics through optimized data products.
  • Support advanced analytics, machine learning, and AI initiatives by providing trusted and scalable data foundations.
  • Evaluate and adopt emerging technologies that improve engineering efficiency and business value.

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