Position 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.
Key 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.
Required Qualifications
•Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related fields.
•10-14 years of IT experience with at least 5+ years in delivery management and technical leadership roles.
•Proven experience leading large-scale Data Engineering and Analytics projects.
Strong understanding of:
· Azure Data Platform
· Databricks
· Azure Data Factory (ADF)
· PySpark
· SQL
· Lakehouse/Data Lake architectures
· Data Governance and Data Quality frameworks
· Experience managing distributed teams and multiple concurrent projects.
· Strong stakeholder management and executive communication skills.
Preferred Qualifications
• Experience leading enterprise-wide data platform modernization or migration programs.
• Experience with Agile, Scrum, DevOps, and CI/CD delivery models.
• Knowledge of AI/ML, advanced analytics, and data product operating models.
•Azure, Databricks, PMP, Agile, or related certifications.
Expected Leadership Scope
•Own delivery portfolio across multiple business domains and projects.
•Accountable for delivery governance, architecture compliance, operational excellence, and strategic roadmap execution.
•Act as the single point of accountability for Data Engineering delivery within the organization.
“Taras Technology, LLC is an EEO/AA Employer: women, minorities, the disabled and veterans are encouraged to apply”
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