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Hybrid

AI TPM

Datametica

AI TPM

Skills

Google Cloud PlatformSQL QueriesPythonData SciencePostgreSQLData AnalysisMachine LearningAIJiraConfluenceNLP / Natural Language ProcessingRisk ManagementAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Pune, Maharashtra, India

Work mode:

Hybrid

Published on:

23 September 2026

What they need


Job Description: Senior Project Manager Data, Cloud & AI/ML

Role Overview

We are seeking a Senior Project Manager (1520 years experience) to lead enterprise-grade Data, Cloud (GCP/Azure), and AI/ML initiatives. You will manage complex delivery programs involving data warehousing, cloud migrations, database upgrades, and advanced analytics/AI solutions across MS SQL Server, PostgreSQL, and BigQuery environments.

Key Responsibilities

  • Project Delivery & Governance: Own end-to-end delivery of Data, Cloud, and AI/ML initiatives across the full lifecycle (initiation, execution, risk management, and closure).
  • Agile & Sprint Governance: Lead Agile sprint cycles, backlog grooming, and daily stand-ups for cross-functional engineering and data science teams.
  • Data Migration & Engineering: Manage complex data warehouse modernizations, ETL/ELT pipeline tracking, and database migrations (On-Prem to Cloud / Cloud-to-Cloud).
  • AI & Modern Tech Delivery: Drive delivery execution for projects involving Python-based processing, Predictive Modeling, NLP, Computer Vision, MLOps, and vector search architectures.
  • Cloud Platform Operations: Manage deliverables on GCP (BigQuery, Dataflow, Vertex AI) and Azure (Azure SQL, Data Factory, Synapse, Azure AI Services).
  • Stakeholder Management: Act as primary liaison between business units, technical teams, and executive leadership; report on project health, risks, and ROI.

Required Skills & Experience

  • 15–20 years of IT project management experience in Data, Cloud, and Analytics domains.
  • Hands-on Delivery: Proven track record in data warehousing, enterprise migrations, and cloud transformations (GCP / Azure).
  • AI & Technical Knowledge: Working understanding of AI/ML lifecycles (MLOps), Python data ecosystems, NLP, and predictive analytics techniques.
  • Databases: Working knowledge of MS SQL Server, PostgreSQL, and BigQuery.
  • Methodologies: Mastery of Agile/Scrum, Jira/Confluence/Azure DevOps, sprint planning, and executive communication.

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