Data Engineer III

SDE III — Data Engineering & Capabilities

About Glance AI

Glance AI is a generative AI-powered commerce platform reimagining how the world shops — less searching for what you want, more discovering who you could be. Live in 140 countries across mobile, connected TVs, and brand stores, our proprietary models integrate with Google's Gemini and Imagen on Vertex AI to deliver hyper-realistic, deeply personal shopping experiences. Part of the InMobi Group and backed by Google, Jio Platforms, and Mithril Capital

The Role

The Data Engineering & Capabilities team builds the intelligence backbone behind everything Glance AI does — personalization, recommendations, multimodal search, experimentation, and AI-driven commerce. As an SDE-3, you'll own large-scale data systems end-to-end: designing them, building them, and running them in production at billions-of-events scal

e.This is a senior, hands-on IC role. You'll work alongside Applied Scientists, ML Engineers, and Platform teams to turn fragmented signals from affiliate feeds, OEM integrations, commerce catalogs, and user interactions into trusted, ML-ready data products.

What You'll Build

• Data pipelines at scale — batch and real-time pipelines with Spark, Flink, Kafka, and Airflow, processing billions of events and catalog updates daily
• User Data Platform — identity resolution and cross-surface signal aggregation across Mobile, TV, OEM, and Commerce; deterministic and probabilistic identity stitching
• Commerce Catalog Platform — ingestion, enrichment, deduplication, and taxonomy frameworks for large, fast-evolving product catalogs
• Feature Store & ML enablement — low-latency feature pipelines serving both model training and online inference
• AI-powered engineering tools — internal agents and copilots for pipeline debugging, SQL generation, data quality triage, and metadata discovery

What We're Looking For

• 5–8 years in Data Engineering, Distributed Systems, or Data Platform development, with proven ownership of large-scale production systems
• Deep hands-on expertise with Spark, Kafka, Flink, and Airflow
• Strong programming in Python plus Scala or Java, and advanced SQL
• Experience with GCP, Big Query, and Databricks; comfort with IaC, cluster management, and cost optimization
• Solid grounding in data modeling, data quality frameworks, lineage, and observability
• Strong system design and distributed systems fundamentals