Technical Program Manager

Hire Type:
Full Time

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, Dev Ops, 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.

• 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 Dev Ops/Git Hub 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/Cloud Watch/Log Analytics, Great Expectations, Monte Carlo, Collibra/Purview.
• Domain exposure:
  Media/Entertainment, Telecom, BFSI, or Retail/E-commerce.