Job Summary

At Kwalee, you'll join a gaming powerhouse that boasts a mobile empire with 1.5 billion+ downloads alongside a thriving PC & Console division that has achieved numerous global chart-topping releases across Steam, Consoles, and Amazon, driving millions of Wishlists. Most recently publishing breakout hits such as The Precinct and Town to City. It's a unique chance to bring your expertise to a global studio that dominates both the mobile, and the indie PC and Console space.

Kwalee's Technology - Data team is looking for a talented Data Engineer to design, build, and maintain Kwalee's data infrastructure pipelines, data lakes, and analytical data stores that power game analytics, BI dashboards, and internal applications.

The Data Engineer will work on large-scale, high-throughput event data and help the broader engineering and product teams move faster with reliable, high-quality data.

This role is based in Bangalore, working onsite 5 days per week, where our daily in-office collaboration fuels creativity and innovation.

Responsibilities

- Design, develop, test, and maintain scalable big data pipelines on Databricks and AWS.
- Build and manage data lake and warehouse models using dbt and Spark, following medallion/lakehouse architecture patterns.
- Own pipeline reliability: monitoring, alerting, incident response, and cost optimisation.
- Collaborate with game developers, analysts, and product teams to translate data requirements into robust infrastructure.
- Support BI and analytics development with well-structured, documented data models.
- Manage AWS data infrastructure including IAM, S3,



Glue, and relevant data services.
- Contribute to data governance practices: data quality checks, schema management, lineage, and access controls.
- Review peers code and contribute to team standards around testing, CI/CD, and deployment via Databricks Asset Bundles.
- Work with stakeholders across the organisation to ensure scalability and performance as data volumes grow.

Required Skills & Experience

- 4-5 years of professional data engineering experience.
- Advanced SQL: Complex transformations, performance tuning, analytical query design.
- Apache Spark: Hands-on production experience with PySpark or Spark SQL; understanding of distributed execution, partitioning, and performance.
- Databricks: Building and operating pipelines on the Databricks platform (Delta Lake, workflows, Unity Catalog).
- Big data pipeline design: Batch and/or streaming at scale; schema evolution; idempotency; reliability patterns.
- AWS infrastructure: Practical experience with S3, IAM, Glue, Lambda, or equivalent services; comfortable reading and modifying infrastructure config.
- Python: For pipeline logic, automation, and data tooling.
- Data engineering best practices: CI/CD for data,



testing strategies (unit + integration), version control (Git), documentation-as-code.
- Team collaboration: Clear communicator; able to work across engineering, analytics, and product; comfortable in async and written communication.
- Basic AI enthusiasm: An interest in how AI/ML fits into modern data platforms and a willingness to learn; you don't need to be an ML engineer.

Nice to Haves

- AWS Redshift or RDS: Experience with Redshift Serverless or RDS as part of a data stack.
- Databricks Asset Bundles: Hands-on with DABs for CI/CD deployment and workplace promotion.
- Dbt: Model authoring, Testing, and Documentation.
- Orchestration tooling: Airflow, Databricks Workflows, or equivalent.
- Streaming: Kafka, Kinesis, or Spark Structured Streaming in production.
- Game analytics or mobile data: Familiarity with high-volume event instrumentation pipelines is a bonus, not a requirement.

What We're Looking For (Beyond the Tech)

You're the kind of engineer who cares about the downstream consumer of your data as much as the pipeline itself. You write code that your colleagues can read and debug at 3 am. You push back on vague requirements and ask what decision does this data need to support. You're comfortable with ambiguity in a fast-moving games company.

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.

📌 Data Engineer (Bengaluru)
🏢 Kwalee
📍 Bengaluru