Data Leader

17 hours ago

Vijayawada, Andhra Pradesh, India beBeeStrategist Full time ₹ 45,00,000 - ₹ 55,00,000
Lead Data Strategist

The role of Lead Data Strategist is a critical component in driving business growth through data-driven insights. As a seasoned leader in data and analytics, you will be responsible for designing and implementing a scalable data strategy that fosters a culture of data-driven decision-making.

Main Responsibilities:

  • Redesign and optimize data models to support large-scale analytics and faster decision-making processes.
  • Define tools and frameworks for data creation, transformation, and consumption across the organization.
  • Build unified data views by integrating behavioral and transactional data into structured, query-optimized flat tables.
  • Own analytics across mobile, web, marketing, product, and operations data streams, ensuring consistent data definitions and scalability.
  • Partner with cross-functional teams to ensure data is democratized and actionable.
  • Establish data governance, quality standards, and best practices for the organization.
  • Drive adoption of self-service analytics and empower teams with the right dashboards, reporting, and insights.
  • Introduce and scale ML-driven insights by collaborating with product and engineering to enable use cases like personalization, predictive modeling, and anomaly detection.
  • Build and mentor a cross-functional analytics team spanning business/operations analytics, marketing/CRM analytics, and product/finance analytics.

Requirements:

  • Strong 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.
  • Proven ability to build and scale analytics teams, with experience in functions such as business/operations, marketing/CRM, and product/finance analytics.
  • Strong business acumen — ability to translate data into actionable insights for growth, retention, and efficiency.
  • Excellent stakeholder management and communication skills, comfortable influencing at the CXO level.

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