2 months ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Design and build scalable batch and real-time data pipelines using Spark, Flink, Kafka, and Airflow.
- Develop reliable ETL/ELT frameworks and data products supporting analytics, experimentation, recommendations, personalization, and AI applications.
- Build user identity resolution, cross-surface signal aggregation, audience, profiling, segmentation, and personalization systems.
- Develop commerce catalog ingestion, enrichment, normalization, deduplication, taxonomy, and quality systems.
- Build feature generation frameworks and low-latency pipelines for ML training and online inference.
- Develop AI-powered internal tools and self-service capabilities for pipeline debugging, data quality triage, SQL optimization, metadata discovery, schema analysis, and cost optimization.
- Own production pipelines and services, including SLAs, monitoring, lineage, alerting, reconciliation, quality checks, incident response, and root-cause analysis.
- Lead architecture and design discussions, drive engineering best practices, mentor junior engineers, and contribute to technical leadership.
Requirements
- 6–10 years of experience in Data Engineering, Distributed Systems, or Data Platform development.
- Strong experience owning large-scale production systems end-to-end.
- Hands-on experience with Apache Spark, Kafka, Flink, Airflow, distributed data processing, and batch and streaming architectures.
- Strong understanding of dimensional modeling, data warehousing, large-scale schema design, complex datasets, and evolving schemas.
- Experience with data validation frameworks, lineage systems, monitoring and alerting, reconciliation pipelines, and CI/CD for data systems.
- Experience with GCP, Databricks, BigQuery, infrastructure as code, cluster management, performance tuning, and cost optimization.
- Strong programming skills in Python, Scala or Java, and SQL.
- Strong understanding of system design, distributed systems, performance optimization, and reliability engineering.
- Preferred experience with product catalogs, affiliate commerce platforms, merchant feeds, search and recommendation systems, identity resolution, audience platforms, Customer 360 systems, user profiling, segmentation, feature stores, training data pipelines, real-time inference data systems, MLOps infrastructure, and LLM-powered developer tools.
Tech Stack
Apache AirflowApache FlinkApache KafkaApache SparkDatabricksGoogle BigQueryGoogle Cloud PlatformJavaPythonScalaSQL
Categories
Data Engineering
About Glance
Glance builds AI-driven commerce and content platforms that surface personalized shopping and media on mobile lock screens, connected TVs, and apps. Its products include Glance, Roposo, and Nostra, partnering with smartphone and TV manufacturers, telecom providers, and brands to enable discovery-led shopping and entertainment, monetized through advertising and commerce. Founded in 2019 and headquartered in Bangalore, it operates as an unconsolidated subsidiary of InMobi, is backed by Google and Jio Platforms, and runs on 450M+ devices.