1. Basic Technical Knowledge (Must Understand, Not Code)
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- Google Cloud: Understands how BigQuery stores data and knows the purpose of Dataflow/DataProc.
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- Data Pipelines: Knows how data moves via ETL tools.
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- Automation: Understands that PySpark or PL/SQL scripts schedule and automate data flows.
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- Reporting Tools: Knows how Power BI or Qlik dashboards deploy reports to business users.
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- Agile Software: High proficiency using Jira (backlogs/epics), Jenkins, or Bitbucket to track tasks.
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2. Business & System Knowledge (Valuable to have)
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- Main Systems: Has managed projects extracting data from systems like SAP, Salesforce, and Dealer Management Systems (DMS).
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- Sales Metrics: Understands terms like sales pipeline, conversion rates, and CRM data.
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- Finance Metrics: Understands revenue tracking, cost reconciliation, and financial auditing needs.
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- Customer Experience: Understands service turnaround times, CSAT, and NPS scores.
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3. Required Work Experience (Must)
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- Data Focus: Has led at least 1 large data warehouse, Lakehouse, or analytics projects from start to finish.
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- Agile Leadership: Has 3 to 5 years of Scrum Master or PMO experience running data teams.
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- Mixed Teams: Experience managing Data Engineers, Modelers, and Dashboard Developers simultaneously.
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- Complex Migrations: Proven experience moving data from older, heavy systems (like SAP) into cloud platforms.
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- The "Translator" Role: Clear ability to translate technical developer updates into simple business language for managers.
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