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.
- 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.
- Lead partner/vendor engagements, SOWs, and third party delivery alignment.
- Build and mentor high-performing teams (engineering managers, data engineers, analysts, QA).
- Lead hiring, capacity planning, performance management, and career development.
- Promote engineering excellence, documentation discipline, and a culture of continuous improvement.
- Own program budgets, resource plans, and cost controls (cloud/Databricks spend).
- Track and report financials: forecasts, burn rates, and variance analysis.
- Support proposals, estimations, and SOW renewals/extensions.
- 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).
- 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.
- 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.
- Bachelor's or Master's in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).