Director of Data Analytics (B2C/D2C)

VAYUZ Technologies; Bengaluru; On-site; INR 6,000,000 - 9,000,000; Full time

Job summary

VAYUZ Technologies is seeking a Director of Analytics to lead the data strategy across the organization. You will redesign data models, unify behavioral and transactional data, and own analytics across mobile, web, marketing, product, and operations data streams.

You will partner with CXOs to democratize data, establish governance, and scale AI/ML-driven insights, including conversational analytics and copilots. Lead a cross-functional team and ensure scalable, reliable data infrastructure.

Qualifications

• 8+ years in data analytics leadership.
• Experience building data marts and enterprise data consumption strategies.
• Strong track record across mobile, web, marketing, product, and operations analytics.
• Deep knowledge of SQL, ETL/ELT, and cloud data warehouses; proficient BI tooling.

Responsibilities

• Lead the next generation of the Data Mart with scalable data models.
• Build unified data views integrating behavioral and transactional data.
• Own analytics across mobile, web, marketing, product, and ops data streams.
• Partner with business and finance to democratize data and establish governance.
• Drive adoption of self-service analytics with dashboards and reporting.
• Introduce and scale AI/ML-driven insights and LLM-powered use cases.
• Collaborate with product/engineering to productionise AI solutions.
• Build and mentor a cross-functional analytics team.

Skills

Data leadership

Data modeling

SQL

ETL/ELT

Cloud data warehouses

Looker

Power BI

Tableau

AI/ML integration

LLM governance

Tools

Snowflake

BigQuery

Redshift

Looker

Power BI

Tableau

Job description

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.

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.
• Successful hiring and scaling of a multi-disciplinary analytics team.
• Retention and growth of top talent within the analytics function.