2 months ago
Bengaluru, IndiaSenior
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 identity resolution, cross-surface signal aggregation, audience, user profiling, and personalization systems.
- Develop ingestion, enrichment, normalization, deduplication, taxonomy, and quality systems for commerce catalogs and merchant feeds.
- Build feature-generation frameworks and low-latency pipelines supporting ML training and online inference.
- Develop AI-powered internal tools for pipeline debugging, data-quality triage, SQL generation, metadata discovery, schema analysis, and cost optimization.
- Own production services and pipelines, including SLAs, observability, lineage, alerting, reconciliation, incident response, and root-cause analysis.
- Lead architecture and design discussions, establish engineering best practices, and mentor junior engineers.
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, and evolving schemas.
- Experience with data validation, lineage, monitoring and alerting, reconciliation pipelines, and data-system delivery practices.
- Experience with GCP, Databricks, BigQuery, infrastructure as code, cluster management, performance tuning, and cost optimization.
- Strong programming skills in Python and Scala or Java, plus SQL.
- Strong understanding of system design, distributed systems, performance optimization, and reliability engineering.
- Preferred experience with product catalogs, affiliate commerce, merchant feeds, search and recommendation systems, identity resolution, audience platforms, customer 360 systems, feature stores, training-data pipelines, real-time inference 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.