1.

Basic Technical

Knowledge (Must Understand, Not Code) - Google Cloud: Understands how BigQuery stores data and knows the purpose of Dataflow/DataProc.

- Data Pipelines: Knows how data moves via ETL tools.
- Automation: Understands that PySpark or PL/SQL scripts schedule and automate data flows.
- Reporting Tools: Knows how Power BI or Qlik dashboards deploy reports to business users.
- Agile Software: High proficiency using Jira (backlogs/epics), Jenkins, or Bitbucket to track tasks.
- Business & System Knowledge (Good to have) - Main Systems: Has managed projects extracting data from systems like SAP, Salesforce, and Dealer Management Systems (DMS).
- Sales Metrics: Understands terms like sales pipeline, conversion rates, and CRM data.
- Finance Metrics: Understands revenue tracking, cost reconciliation, and financial auditing needs.
- Customer Experience:



Understands service turnaround times, CSAT, and NPS scores. 3.

Required Work

Experience (Must) - Data Focus: Has led at least 1 large data warehouse, Lakehouse, or analytics projects from start to finish.

- Agile Leadership: Has 3 to 5 years of Scrum Master or PMO experience running data teams.
- Mixed Teams: Experience managing Data Engineers, Modelers, and Dashboard Developers simultaneously.
- Complex Migrations: Proven experience moving data from older, heavy systems (like SAP) into cloud platforms.
- The "Translator" Role: Clear ability to translate technical developer updates into easy business language for managers.

📌 GCP Project Manager (Mumbai)
🏢 Tech Mahindra
📍 Mumbai