Senior Program Manager (Data + AI)
About the role
We are hiring a Program Manager to own end-to-end delivery of large, complex Data & AI programs for enterprise customers, with a focus on US telecom accounts. You will lead a team of about 30, run large-scale migration programs onto the Databricks platform, and manage data and AI solutions around telecom billing and invoicing.
This is a customer-facing leadership role. You will be the primary point of contact for senior customer stakeholders and will steer delivery across a multi-party ecosystem of customer IT, business teams, product vendors and partners.
Key responsibilities
Program delivery
• Own scope, schedule, budget, quality and risk for multi-workstream Data & AI programs of enterprise scale.
• Plan and run large-scale migrations from legacy data platforms (on-prem warehouses, Hadoop, legacy ETL) to the Databricks Lakehouse, covering assessment, wave planning, code conversion, data validation, cutover, reconciliation and legacy decommissioning.
• Set up program governance: steering committees, RAID logs, status reporting, change control and escalation paths.
• Track delivery health with clear metrics (milestones, burn, defects, SLAs) and act early on slippage.
Telecom billing and invoicing
• Lead data and AI initiatives across the billing lifecycle: usage/rating data, invoice generation, revenue assurance, dispute and adjustment analytics.
• Translate billing and invoicing business processes into data requirements, data models and reconciliation controls.
• Ensure data accuracy and auditability for financially sensitive billing data.
Customer management
• Act as the primary delivery contact for US customer leadership (Director, VP and CXO level).
• Manage a complex ecosystem of customer IT and business teams, third-party vendors, platform partners and other SIs.
• Run business reviews (weekly, monthly, QBR), manage expectations and handle escalations with composure.
• Spot account growth opportunities and support proposals, SOWs and change requests.
People leadership
• Lead a team of about 30 across data engineering, ML, architecture, QA and analysis, working across US and India time zones.
• Drive hiring, onboarding, allocation, performance and career growth for the team.
• Build a delivery culture of ownership, quality and clear communication.
Must-have qualifications
• 12–18 years in IT services or product delivery, with 5+ years managing large Data & AI programs end to end.
• Proven delivery of large, complex, enterprise-grade data programs (multi-workstream, multi-million-dollar, high visibility).
• Has led at least one large-scale, enterprise migration to the Databricks platform end to end (multi-TB to PB data, hundreds of pipelines, phased cutover with parallel runs).
• Domain experience in telecom billing and invoicing processes (rating, invoicing, revenue assurance, billing data reconciliation).
• Has led teams of 25–35 people, including onsite–offshore delivery models.
• Has managed complex customer ecosystems with multiple vendors and stakeholders, preferably for US customers.
• Excellent articulation and communication, written and verbal; confident presenting to senior customer leadership.
• Sound grasp of modern data architecture: lakehouse, ETL/ELT, data governance, cloud platforms (AWS, Azure or GCP).
• Working knowledge of AI/ML and GenAI delivery (MLOps, model deployment, use-case scoping).
• Strong command of delivery frameworks (Agile/Scrum, SAFe or hybrid) and program financials.
• Bachelor's degree in Engineering or Computer Science; MBA a plus.
Technology skills
The candidate need not code daily, but must be able to review designs, challenge estimates and guide architects on the areas below.
Area
Skills expected
Databricks platform
Lakehouse architecture, Delta Lake, Unity Catalog, Databricks SQL and SQL Warehouses, Workflows/Jobs, Delta Live Tables, Photon, cluster and cost management
Migration sources
Teradata, Oracle, Netezza, SQL Server, Hadoop/Cloudera (Hive, Spark), Informatica, DataStage, SSIS, SAS
Migration approach
Discovery and inventory, lift-and-shift vs re-engineer decisions, SQL/ETL code conversion, data validation and reconciliation, parallel runs, cutover and rollback planning
Data engineering
Apache Spark (PySpark, Spark SQL), batch and streaming (Structured Streaming, Kafka, Auto Loader), medallion architecture
Governance and security
Unity Catalog access control, data lineage, data quality frameworks, PII handling for billing and customer data
AI/ML on Databricks
MLflow, Feature Store, Model Serving, Mosaic AI / GenAI use cases
Cloud
Databricks on AWS, Azure or GCP; object storage, networking and IAM basics
DevOps and FinOps
CI/CD with Databricks Asset Bundles, Git, Terraform; DBU cost monitoring and optimisation
Certifications (preferred)
Databricks Certified Data Engineer (Associate/Professional) or Databricks Lakehouse Fundamentals
Good to have
• Certifications: PMP, PgMP, SAFe (RTE/SPC), or Databricks / cloud certifications.
• Exposure to telecom BSS/OSS stacks and billing platforms (e.g., Amdocs, Netcracker, Ericsson, CSG).
• Experience with Databricks migration accelerators and code-conversion tools (e.g., Lakebridge / BladeBridge or partner-built converters).
• Prior onsite stint or extensive travel experience with US customers.
• Experience in pre-sales, solutioning or account mining for data programs.
