Role: Data Engineering Lead

Function: Data Engineering

Location: Navi Mumbai, Maharashtra

Type: Full-time

Compensation: Not specified

Industry: AI/ML, Consumer Technology

About Company

The company is building the AI layer for Bharat at India-scale. Backed by partnerships with global tech leaders like Meta and Google, the team is creating AI that serves the entire Indian user base—across languages, contexts, and daily needs. This is AI designed for real adoption, not experiments.

They bring a rare combination of deep India-first AI capability and unmatched India-scale distribution. The focus is a platform-and-product stack that makes AI useful, reliable, and safe for everyday consumers. It’s engineered from day one for massive scale—100M+ users early and 1B-ready constraints on latency, cost, reliability, and safety.

If you want to be part of a fast-moving, high-ambition team building technology with real-world reach, this is that opportunity. The culture emphasises engineering excellence, strong collaboration, and tangible impact across sectors that matter to India—while building toward a category-defining consumer AI experience.

Position Overview

You'll design and implement the core data infrastructure that powers a multimodal, multilingual consumer AI platform serving 100M+ users. You'll build advanced analytics frameworks, real-time streaming systems, and monitoring infrastructure with 1B-ready constraints on latency, cost, and reliability. This role offers direct ownership of data systems that enable AI model training, user behavior analysis, and product optimization at unprecedented scale in the Indian market.

Role & Responsibilities

• Design and implement advanced analytics frameworks and statistical models to derive insights from user behavior and AI interaction patterns
• Build real-time streaming analytics systems using Apache Spark and Apache Flink for continuous data analysis
• Develop comprehensive business intelligence dashboards and KPI tracking systems for product performance optimization
• Architect complex analytical queries and data models in BigQuery for deep-dive analysis of multimodal AI interactions
• Build product data engineering pipelines to track user journeys, feature adoption, and conversion funnels across the AI platform
• Design and implement data infrastructure for generative AI model training, fine-tuning, and inference monitoring at scale
• Create automated reporting systems and analytical pipelines for business metrics and operational intelligence
• Lead predictive analytics initiatives and A/B testing frameworks to drive data-driven product decisions
• Implement advanced data quality monitoring, anomaly detection, and statistical validation systems for production analytics

Must Have Criteria

• 10+ years of hands-on data engineering experience with strong data analytics background
• 3+ years of solid prior experience working with Databricks for large-scale data processing
• Proven experience building data systems processing petabyte-scale datasets with billions of events per day
• Expert-level proficiency in Python and SQL for data pipeline development
• Hands-on experience with Apache Airflow for workflow orchestration and pipeline management
• Proven experience with Apache Spark and Apache Flink for batch and stream processing
• Strong experience with Google BigQuery for data warehousing and analytics

Nice to Have

• Prior hands-on experience with GraphQL for data querying and API integration
• Experience with AI/ML data pipelines and model serving infrastructure
• Background in building data systems for conversational AI or chatbot platforms
• Previous work in startup or high-growth environments with rapid iteration cycles

What We Offer

• Opportunity to build data infrastructure for India's largest consumer AI platform
• Work with cutting-edge AI technology and massive scale data challenges
• High-ownership environment with direct impact on product outcomes
• Competitive compensation and equity in a high-growth AI company
• Collaborate with world-class AI/ML engineers and product teams