Data Engineering Program Manager

Snowflake:
Data Warehousing, Snowpark, Data Sharing, Performance Optimization, Security & Governance.

Databricks:
Lakehouse Architecture, Delta Lake, Unity Catalog, Spark / PySpark, ML & AI workloads.

Cloud Platforms: AWS preferred;
Azure and GCP exposure beneficial.

Data Management:
Data Modeling, Data Governance, Master Data Management, Data Quality.

PMP, PgMP, SAFe Program Consultant, or SAFe Agilist certification.

Snowflake certification and/or Databricks certification.

Experience leading AI/GenAI-enabled data programs.

Experience with healthcare compliance requirements such as HIPAA, GxP, and FDA-regulated environments.

Lead end-to-end delivery of enterprise data engineering and analytics programs.

Define program roadmap, milestones, dependencies, risks, and governance structures.

Manage multiple concurrent projects spanning data ingestion, transformation, warehousing, analytics, and AI/ML initiatives.

Drive executive-level status reporting and steering committee governance.

Partner with business and IT leaders to define enterprise data strategies leveraging Snowflake and Databricks.

Oversee platform modernization, data lakehouse, and cloud migration initiatives.

Ensure alignment between business objectives, architecture standards, and technology roadmaps.

Coordinate global teams of architects, data engineers, cloud engineers, analysts, and product owners.

Manage Agile delivery across multiple work streams.

Track program KPIs including schedule, financials, quality, productivity, and business outcomes.

Ensure successful transition from project implementation to steady-state operations.

Serve as the primary liaison between business leaders, data teams, architecture groups, and external partners.

Facilitate steering committee reviews and executive presentations.

Drive decision-making and issue resolution across organizational boundaries.

Ensure compliance with enterprise data governance standards.

Oversee data quality, metadata management, security, privacy, and regulatory requirements.

Drive adoption of data cataloging and lineage frameworks.

Manage program budgets and forecasts.

Oversee vendor performance and contractual deliverables.

Track business value realization and ROI for data initiatives.

Identify opportunities to leverage AI/GenAI, automation, and advanced analytics.

Promote engineering best practices and operational excellence.

Drive platform optimization, Fin Ops, and cost governance initiatives.