Technical Program Manager / Senior Delivery Manager – Data & AI Platforms

Technical Program Manager / Senior Delivery Manager – Data & AI Platforms

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Role Summary

Technical Program Manager / Senior Delivery Manager

strategic technology leader

Key Responsibilities

• Lead, mentor, and drive

  150+ technical professionals

  across data engineering, cloud, analytics, AI/ML, and application teams.
• Define and manage

  program vision, scope, roadmap, and delivery strategy

  for large-scale data and AI transformation initiatives.
• Oversee

  end-to-end execution

  of Data & AI platform programs including cloud data warehouse design (e.g., Snowflake, Redshift, Synapse), AI/ML pipeline implementation, and analytics modernization.
• Partner with internal stakeholders to ensure alignment of technology delivery with business and operational objectives.
• Establish and maintain

  program governance

  —track milestones, budgets, dependencies, risks, and outcomes.
• Champion best practices in

  Agile/Hybrid delivery

  , DevOps, and continuous improvement.
• Translate complex technical concepts (data architecture, AI/ML workflows, data models) into business-oriented outcomes.
• Ensure

  data security, governance, and compliance

  are embedded in all deliverables.
• Manage and optimize resource utilization, workforce planning, and team performance across multiple project streams.
• Foster a

  culture of innovation, accountability, and technical excellence

  within the team.
• Provide strategic guidance to architects, engineers, and project managers to ensure scalability and sustainability of solutions.

Required Qualifications & Experience

• Bachelor’s or Master’s degree in

  Computer Science, Engineering, or Information Systems

  .

• 10–15 years

  of IT delivery and

  program management experience

  , with a focus on

  Data Platforms, Cloud, or AI/ML programs

  .
• Proven background as a

  Data Architect or Solution Architect

  with experience designing or overseeing cloud data platforms (Snowflake, AWS, Azure, or GCP).
• Demonstrated success managing

  large-scale delivery teams (100–150+ resources)

  across multiple projects and geographies.
• Strong expertise in

  data engineering concepts

  (ETL/ELT, data modelling, data Lakehouse architectures).
• Familiarity with

  AI/ML development lifecycle

  , from model design to deployment and monitoring.
• Excellent

  stakeholder management

  , communication, and leadership skills with the ability to influence both technical and non-technical audiences.
• Proven experience with

  program governance frameworks

  , dashboards, reporting, and risk management.
• Certifications such as

  PMP, PgMP, Agile/ScrumMaster, or Cloud Architect (AWS/Azure/GCP)

  are an advantage.

Desired Skills

• Hands-on exposure to

  data integration and AI/ML platforms

  (e.g., Databricks, Sage Maker, Azure ML, Vertex AI).
• Experience with

  data platform modernization, migration, or analytics transformation

  programs.
• Background in

  multi-vendor

  or

  global delivery environments

  .
• Experience in

  change management

  ,

  adoption programs

  , and

  user enablement

  for analytics or AI platforms.

Key Competencies & Attributes

• Strong

  strategic and analytical mindset

  with ability to manage complex, multi-stream programs.
• Technically credible — able to engage deeply with architects and engineering teams.
• Excellent

  organization, prioritization, and stakeholder engagement

  skills.

• Results-oriented leader

  with a focus on quality, performance, and efficiency.
• Demonstrated

  mentorship and team-building

  capability at scale (100+ members).
• Passion for

  data-driven innovation

  ,

  AI enablement

  , and

  continuous learning

  .

Deliverables & Success Metrics

• Successful delivery of Data & AI programs within schedule, scope, and budget.
• Improved platform maturity and measurable business outcomes (e.g., reduced latency, better insights, automation).
• Strong team performance and retention across 150+ technical resources.
• High stakeholder satisfaction and transparent program governance.
• Adoption and utilization of Data & AI solutions across multiple business functions.

Reporting & Collaboration

• Reports to:

  Director / VP – Delivery & Operations, TechStar Group

• Interfaces with:

• Data Engineering, Cloud, and AI/ML Teams
• Product and Business Leads
• Solution Architects and Technical Delivery Managers
• PMO, HR, and Vendor Management