Role Responsibilities-
As the Director of Analytics, you will be:
- 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 and 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: Ensure consistent data definitions and scalability.
- Partner with business, product, marketing, CRM, operations, and finance teams: Ensure data is democratized and actionable. Establish data governance, quality standards, and best practices for the organization.
- Drive adoption of self-service analytics: Empower teams with the right dashboards, reporting, and insights.
- Introduce and scale AI/ML-driven insights:
- Collaborate with product and engineering to enable LLM-powered use cases, such as conversational analytics and decision copilots.
- Enable ML-driven use cases such as personalization, predictive modeling, and anomaly detection.
- Build and mentor a cross-functional analytics team: The team will span business/operations analytics, marketing/CRM analytics, and product/finance analytics.
- Partner with engineering leadership: Ensure scalability, reliability, and efficiency of the data infrastructure.
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What We’re Looking For-
Experience
- 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, including SQL, ETL/ELT, cloud data warehouses like Snowflake/BigQuery/Redshift, and BI tools like Looker/PowerBI/Tableau.
AI Expertise
- Experience working with or enabling AI/ML and LLM-based use cases, including building data pipelines for AI applications, supporting use cases such as process automation and conversational analytics, and partnering with engineering to productionise AI-driven solutions.
ML Competency
- Familiarity with machine learning workflows, including data pipelines for ML, feature engineering, and model monitoring, with the 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 and ability to translate data into actionable insights for growth, retention, and efficiency.
- Excellent stakeholder management and communication skills, comfortable influencing at the CXO level.
KPIs / Success Metrics
Success in this role will be measured by:
Data Infrastructure Scale
- Launch of next-gen data mart within defined timelines.
- Reduction in data processing and reporting times.
- Uptime and reliability of data pipelines and consumption layers.
Adoption Impact
- % of the organization actively using self-service analytics tools.
- Increase in cross-team usage of standardized data views across product, marketing, finance, and operations.
- Reduction in ad-hoc analytics requests due to robust self-service solutions.
- LLM-powered use cases successfully deployed to production.
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.