SDE-3 Data Engineering and Capabilities Team

About the Team

At Glance, we are building a first-of-its-kind generative AI-powered commerce platform that transforms how users discover and shop across mobile surfaces, TV, and brand stores.

The Data Engineering Capabilities Team is responsible for building the intelligence backbone that powers personalization, recommendations, multimodal search, experimentation, analytics, and AI-driven commerce experiences. We bring together data from affiliate feeds, OEM integrations, commerce catalogs, user interactions, and transaction systems to create trusted, scalable, and ML-ready data products.

As an SDE-3 Data Engineer, you will play a key role in building and scaling the foundational data systems that power Glances next generation of AI products.

Role Overview

We are looking for a highly skilled and hands-on Data Engineer to own the design, development, and operation of large-scale data platforms and capabilities.

You will work closely with Applied Scientists, ML Engineers, Product Managers, Analytics teams, and Platform Engineers to build reliable data pipelines, feature stores, identity systems, catalog infrastructure, and self-service capabilities that accelerate experimentation and machine learning development.

You will be expected to independently drive complex technical initiatives from design through production while maintaining high standards of quality, scalability, and operational excellence.

Key Responsibilities

Data Platform Development

- Design and build scalable batch and real-time data pipelines using Spark, Flink, Kafka, and Airflow.
- Develop data products that support analytics, experimentation, recommendation systems, personalization, and AI applications.
- Build and maintain highly reliable ETL/ELT frameworks processing billions of events and catalog updates.

User Data Platform





- Develop systems for user identity resolution and cross-surface signal aggregation across Mobile, TV, OEM, and Commerce ecosystems.
- Build datasets and services that support user profiling, audience creation, segmentation, and personalization.

- Contribute to deterministic and probabilistic identity stitching frameworks.

Commerce Catalog Platform

- Build ingestion and enrichment pipelines for affiliate feeds, merchant catalogs, D2C integrations, and product metadata.

- Design scalable schemas and taxonomy frameworks for large and evolving commerce catalogs.

- Develop catalog quality, deduplication, normalization, and enrichment systems.

Feature Store ML Enablement

- Build reusable feature generation frameworks for ML and recommendation systems.

- Create low-latency feature pipelines serving training and online inference workloads.

- Partner with Applied Scientists to improve feature discoverability, governance, and reusability.

AI-Powered Engineering Capabilities

- Develop internal AI-powered tools, agents, and self-service platforms that improve developer productivity.

- Pipeline debugging

- Data quality triage

- SQL generation and optimization

- Metadata discovery

- Schema change analysis

- Cost optimization recommendations

Reliability Operational Excellence

- Own production services and pipelines with robust SLAs.

- Build observability into every layer through monitoring, lineage, alerting, reconciliation, and quality checks.

- Participate in incident response, root-cause analysis, and operational reviews.

- Continuously improve platform reliability, performance, and cost efficiency.

Technical Leadership

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 SDE III - Data Engineering (Bengaluru)
🏢 Glance
📍 Bengaluru