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.

2. Business & System Knowledge (Positive 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 simple business language for managers.

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