At VIDA we’re building the future of digital identity. As a Data Engineer you’ll work across the stack—from platform and infrastructure to data pipelines and end-user tooling. You’ll help us modernize our batch ETLs and lead our push into streaming and real-time fraud detection. We run on AWS and make extensive use of Scala Spark, dbt, and Terraform.Responsibilities
Build and expose the data lake/lakehouse so teams can understand business and product performance and make better decisions.
Design and evolve a data platform that enables scientists and analysts to query, model, and ship features and product metrics.
Develop scalable and reliable batch and streaming pipelines that ingest from wide-ranging sources and land trusted datasets.
Maintain and fix existing ETLs, improving reliability, observability, and cost while planning secure backfills and replays.
Model curated layers and maintain transformation logic (e.g., dbt), including testing, documentation, and data quality.
Build with Infrastructure as Code (e.g., Terraform) and contribute to CI/CD and deployment practices.




Partner with Engineering, and Data Science to deliver low-latency signals and features for real-time decisioning.
Contribute to internal tools, reusable components, and straightforward dashboards that unblock self-service.

Requirements
Solid engineering foundation with 5+ years of relevant experience in data engineering and/or distributed systems.
Hands-on work building data pipelines (batch and/or streaming) using at least one distributed framework (e.g., Spark, Kafka, Flink).
Comfortable with SQL and a transformation framework (e.g., dbt or similar).
Familiarity with AWS services for data (any mix of S3, EMR/Glue, Kinesis/MSK, Lambda, Redshift/Athena) or equivalent cloud experience.
Exposure to workflow orchestration (e.g., Airflow).
Experience using Terraform (or similar IaC) to manage data/platform resources.
Ownership mindset, focus on reliability, and enjoyment of collaborati

📌 Data Engineer Bengaluru
🏢 VIDA
📍 Bengaluru