Data Visionary

2 days ago

Belgaum, Karnataka, India beBeeAnalytics Full time ₹ 45,00,000 - ₹ 55,00,000
Lead Data Strategist

This role requires a seasoned data leader to build and execute a unified data strategy that supports business growth and decision-making. The ideal candidate will have a strong track record of designing and implementing data marts, defining enterprise-wide data consumption strategies, and driving adoption of self-service analytics.

The Lead Data Strategist will partner with cross-functional teams to integrate behavioral and transactional data into structured, query-optimized flat tables that support diverse analytics use cases. They will also establish data governance, quality standards, and best practices for the organization.

Responsibilities:
  • Develop and execute a comprehensive data strategy that aligns with business objectives.
  • Design and implement data marts that support large-scale analytics and faster decision-making.
  • Define enterprise-wide data consumption strategies that ensure consistent data definitions and scalability.
  • Establish data governance, quality standards, and best practices for the organization.
  • Partner with cross-functional teams to drive adoption of self-service analytics.
Requirements:
  • 8+ years in data & analytics leadership with proven success in building data marts and defining enterprise-wide data consumption strategies.
  • Strong track record of running analytics across mobile, web, marketing, product, and operations data ecosystems.
  • Deep technical expertise in data modeling, flat table structures, and query optimization for large-scale systems.
  • Hands-on experience with both behavioral and transactional data, and integrating them into a single analytics layer.
  • Strong knowledge of modern data stack (SQL, ETL/ELT, cloud data warehouses like Snowflake/BigQuery/Redshift, BI tools like Looker/PowerBI/Tableau).
  • ML Competency: Familiarity with machine learning workflows (data pipelines for ML, feature engineering, model monitoring) and ability to guide data scientists in building predictive/ML models.
KPIs / Success Metrics:
  • Data Infrastructure & Scale
  • Launch of next-gen data mart within defined timelines.
  • Reduction in data processing and reporting times (e.g.,

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