
Analytics Strategist
1 day ago
As a key player in shaping our data strategy, you will be responsible for leading the charge in building scalable infrastructure and creating a high-performing analytics organization.
Key Responsibilities:- Develop and implement a next-generation data mart that supports large-scale analytics and faster decision-making.
- Define the tools and frameworks for data creation, transformation, and consumption across the company.
- Design 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.
- Collaborate 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: 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.
- 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 (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.
- Launch of next-gen data mart within defined timelines.
- Reduction in data processing and reporting times (e.g.,
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