Engineering Manager Ii- Data Analytics and Recommendations

Uber Uber · Consumer · Bangalore, India · Engineering

Engineering Manager for Uber's Ads organization in India, leading the Reporting and Recommendations team. This role focuses on building foundational data, insights, and personalization systems for advertising across Mobility, Delivery, and Grocery. The team owns platforms for advertisers to understand performance, optimize spend, and reach audiences through scalable reporting, recommendations, and datamart solutions. Requires strong leadership in data-intensive systems and experience with recommendation/personalization systems.

What you'd actually do

  1. Foster a collaborative, inclusive, and high-performance culture that values creativity, ownership, and continuous learning.
  2. Provide mentorship, clear career paths, and development opportunities to help engineers grow as technical and thought leaders.
  3. Promote a culture of technical excellence — emphasizing strong design principles, code quality, and peer reviews.
  4. Lead design and delivery of scalable data, reporting, and recommendation platforms used across Ads products and LOBs.
  5. Drive the architectural vision for multi-LOB insights generation, personalization, and measurement frameworks.

Skills

Required

  • software engineering experience
  • engineering management
  • backend systems
  • data-intensive systems
  • data platforms
  • reporting platforms
  • recommendation systems
  • personalization systems
  • distributed systems
  • real-time data processing
  • batch data processing
  • analytics
  • Spark
  • Hive
  • Pinot
  • Kafka
  • Flink
  • Presto
  • leadership
  • communication skills

Nice to have

  • AdTech
  • attribution systems
  • measurement systems
  • product sense
  • building horizontal data solutions
  • managing hybrid global teams

What the JD emphasized

  • 14+ years of overall software engineering experience, including 3+ years in engineering management leading backend and data-intensive systems.
  • Proven track record in designing and scaling data or reporting platforms, preferably in e-commerce, advertising, or On-Demand Delivery (OFD) domains.
  • Deep technical expertise in distributed systems, real-time and batch data processing, and analytics (e.g., Spark, Hive, Pinot, Kafka, Flink, Presto).
  • Experience working with recommendation or personalization systems and collaborating with ML/Applied Science teams.