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 (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: Transparent ability to translate technical developer updates into simple business language for managers.

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