Technical Project Manager

Job Title

Technical Project Delivery Manager Enterprise Data Solutions

Location

Bangalore

Experience

8–10+ years (with strong technical delivery background)

Role Summary

Technical Project Delivery Manager

business stakeholders, data engineers, architects, and AI teams

Key Responsibilities

Project & Program Delivery

• Own

  end-to-end delivery

  of large-scale

  enterprise data and AI programs

  across multiple workstreams.
• Ensure

  on-time, on-budget, and high-quality

  delivery using Agile / Hybrid methodologies.
• Drive sprint planning, PI planning, backlog grooming, release management, and delivery governance.

Technical Leadership

• Lead delivery of solutions using:

• Big Data & Analytics:

  Hadoop, Spark, Kafka, Hive, Presto

• Cloud Platforms:

  AWS, Azure. GCP (data & AI services)

• Modern Data Platforms:

  Databricks, Snowflake

• AI & Advanced Analytics:

  GenAI, LLMs, Agentic AI frameworks, MLOps
• Collaborate with architects to ensure

  scalable, secure, and performant

  data architectures.
• Review technical designs, data pipelines, AI workflows, and integration approaches from a delivery standpoint.
• Ensure adherence to enterprise standards for

  data governance, security, privacy, and compliance

  .

Stakeholder & Business Management

• Act as the primary interface with

  business leaders, product owners, and executive sponsors

  .
• Translate business requirements into

  technical delivery plans

  and measurable outcomes.

Team & People Leadership

• Lead and coordinate cross-functional teams
• Mentor team members on delivery excellence, agile best practices, and technical awareness.
• Foster a culture of

  accountability, innovation, and continuous improvement

  .

Governance, Risk & Quality

• Establish delivery governance, KPIs, and metrics for program health.
• Proactively identify and manage

  technical, delivery, and operational risks

  .
• Ensure robust

  testing, validation, and production readiness

  for data and AI solutions.
• Drive post-implementation reviews and continuous optimization.

Required Skills & Qualifications

Technical Skills

• Strong understanding of

  big data technologies and ecosystems

  (Hadoop, Spark, Kafka, etc.)
• Hands-on knowledge of

  cloud platforms: AWS

  (S3, EMR, Glue, Redshift, SageMaker) and/or

  Azure

  (Data Factory, Synapse, Databricks, Azure ML)
• Experience delivering solutions on

  Snowflake/Databricks

  and modern cloud data warehouses.
• Understanding of

  data warehousing concepts

  , data lakes, lakehouse architectures, and ETL/ELT processes
• Working knowledge of

  GenAI, LLMs, Agentic AI concepts

  , and AI solution lifecycle.
• Familiarity with

  data ingestion, ETL/ELT, streaming, data modelling, and MLOps

  .
• Knowledge of

  data governance, data quality frameworks

  , and master data management

Delivery & Management Skills

• Proven experience delivering

  large, complex enterprise data programs

  .
• Strong Agile / Scrum / SAFe delivery expertise.
• Excellent planning, estimation, risk management, and dependency management skills.
• Ability to manage multiple projects and priorities simultaneously.

Soft Skills

• Strong communication and executive-level presentation skills.
• Strategic thinking with strong attention to delivery detail.
• Customer-centric and outcome-driven mindset.

Preferred Qualifications

• Bachelor’s degree in computer science, Information Systems, Engineering, or related field; Master's degree preferred
• PMP, Scrum Master, or Agile certifications.
• Cloud certifications (AWS, Azure, Databricks, Snowflake).
• Experience in

  AI-driven enterprise transformation programs

  .