Chief Analytics Architect

15 hours ago

Palakkad, Kerala, India beBeeDataStrategist Full time ₹ 45,00,000 - ₹ 55,00,000

About this Role

We are a high-growth startup building products at scale that impact millions of users daily. As we prepare for the next phase of growth, data will be at the heart of every decision – powering product, marketing, operations, and finance.

As the Data Strategist, you will lead the charge in shaping our data strategy, building scalable infrastructure, and creating a high-performing analytics organization.

Key Responsibilities

  • Lead the next generation of our Data Mart: Redesign and optimize data models to support large-scale analytics and faster decision-making.
  • Define the tools & frameworks for data creation, transformation, and consumption across the company.
  • Build unified data views: Integrate behavioral and transactional data into structured, query-optimized flat tables that support diverse analytics use cases.
  • Own analytics across mobile, web, marketing, product, and operations data streams, ensuring consistent data definitions and scalability.
  • Partner with product, marketing, CRM, operations, and finance teams to ensure data is democratized and actionable.
  • Establish data governance, quality standards, and best practices for the org.
  • Drive adoption of self-service analytics and empower teams with the right dashboards, reporting, and insights.
  • Introduce and scale ML-driven insights: Collaborate 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.
  • Partner with engineering leadership to ensure scalability, reliability, and efficiency of the data infrastructure.

KPIs / Success Metrics

  • Data Infrastructure & Scale
  • Launch of next-gen data mart within defined timelines.
  • Reduction in data processing and reporting times (e.g., < 5 mins refresh for key dashboards).
  • Uptime and reliability of data pipelines and consumption layers.
  • Adoption & Impact
  • % of org actively using self-service analytics tools.
  • Increase in cross-team usage of standardized data views (product, marketing, finance, operations).
  • Reduction in ad-hoc analytics requests due to robust self-service solutions.
  • Data Quality & Governance
  • % improvement in data accuracy and consistency across sources.
  • Establishment and adoption of data governance frameworks.
  • Team & Leadership
  • Successful hiring and scaling of a multi-disciplinary analytics team.
  • Retention and growth of top talent within the analytics function.

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