Senior Technical Program Manager with Data Engineering

We are seeking a senior Technical Program Manager to lead complex, multi-workstream data platform initiatives using Databricks and modern ETL/ELT patterns. The TPM will drive strategy, delivery, and governance across data engineering, analytics, and platform modernization efforts—managing roadmaps, budgets, risks, and stakeholder communication while enabling high-performing teams to deliver business value at scale.

Program Leadership & Strategy

Own end-to-end program strategy, roadmap, and execution for Databricks-centric data platform initiatives. Translate business outcomes into measurable OKRs/KPIs and delivery milestones. Orchestrate cross-functional delivery across data engineering, platform, DevOps, QA, and security teams.

Delivery Management

Establish delivery governance (RAID, change control, dependencies, risk burndown) and ensure on-time, on-budget delivery. Drive Agile at scale (Scrum/Kanban/SAFe), sprint health, throughput, and release management. Define and enforce SLAs/SLOs for data pipelines, batch/streaming jobs, and analytics products.

Technical Program Ownership (Databricks/ETL) Guide solution direction for Databricks (Apache Spark, Delta Lake, Unity Catalog), ETL/ELT flows, and data warehousing. Oversee modernization/migration programs (onprem to cloud), cost optimization (cluster policies, job scheduling), and performance tuning. Ensure robust CI/CD for data pipelines, IaC for platform components, and environment parity across Dev/Test/Prod.

Data Architecture & Governance

Partner with architects on data models, lakehouse patterns, CDC, and medallion architecture. Implement data quality, lineage, cataloging, and access controls (e.g., Unity Catalog, row/column-level security). Ensure compliance with data privacy and regulatory requirements (e.g., PII/GDPR as applicable).

Stakeholder & Customer Management · Engage senior business stakeholders, product owners, and client leadership; manage expectations and executive reporting. Convert ambiguous requirements into clear program epics with acceptance criteria and success measures.

Required Skills

• Program Management Enterprise-scale program ownership, governance, RAID management, executive communication.
• Strong backlog management, prioritization, and stakeholder alignment.
• Proven delivery of multi-workstream, multi-vendor programs.
• Databricks & Data Engineering Databricks (Spark, Delta Lake, Unity Catalog, Job clusters), performance tuning & cost governance.
• ETL/ELT using Azure Data Factory / Synapse Pipelines / dbt / Airflow / Informatica (any strong combo).
• Strong SQL & practical Python for data workflows; CI/CD (Azure DevOps/GitHub Actions/Jenkins).
• Data warehousing/lakehouse patterns; batch & streaming (e.g., Structured Streaming).
• Cloud (one or more) · Azure (preferred), AWS, or GCP—including storage, compute, IAM, networking basics, and monitoring.
• Data Governance & Quality · Data cataloging/lineage, DQ frameworks, access control, secrets management, auditability.
• Leadership & Communication · Team leadership (15–40 members), mentorship, and conflict resolution.
• Clear, concise communication with senior business and technical audiences. --- Good-to-Have · Certifications: PMP/Prince2, SAFe/CSM, Databricks Data Engineer Professional, Azure/AWS cloud certs. · Tools: Terraform/Bicep, Datadog/CloudWatch/Log Analytics, Great Expectations, Monte Carlo, Collibra/Purview. · Domain exposure: Media/Entertainment, Telecom, BFSI, or Retail/E-commerce.