We are growing our Data & AI practice, which delivers cloud data platforms, data modernisation and migration, analytics and AI-enabled engineering for global enterprise clients. You will work in cross-functional teams on long-term engagements, using contemporary cloud technologies and AI-assisted engineering practices.

Role Summary

Builds, tests and runs data pipelines and data platforms end to end on AWS from ingestion to business-ready data – including migration of legacy data workloads. One JD covering three levels.

Roles & Responsibilities

- Build ingestion, transformation and data-quality pipelines (batch and incremental)
- Model and manage data in layered lakehouse / warehouse architectures
- Develop with dbt, PySpark and SQL; orchestrate with Apache Airflow
- Migrate and refactor legacy SQL, workflows and scripts to modern tools, using AI-assisted conversion
- Configure data platform components on client environments; deploy through CI/CD
- Tune performance and cost; support parallel runs and go-lives
- Senior / Lead:



set coding standards, review code, plan work, mentor engineers

Mandatory Skills

- Python, PySpark, advanced SQL
- dbt and Apache Airflow
- AWS: S3, Glue, Athena, EMR; Redshift a plus
- Data modelling and upsert / deduplication patterns
- Git and CI/CD practices
- Data-quality testing

Nice to Have

- Apache Iceberg / Delta / Hudi
- Customer data platforms (CDP) or marketing data
- Legacy workflow / ETL tools and SQL dialects (Presto, Hive)
- Streaming (Kafka, Kinesis)
- AI coding assistants (Claude Code, GitHub Copilot, Amazon Q Developer)

Also Expected Clear communication with remote client stakeholders across time zones; Comfortable using AI coding and productivity tools, and reviewing AI-generated work critically; Agile ways of working; ownership and accountability. Certifications: AWS Certified Data Engineer – Associate (preferred).

📌 Lead / Senior Data Engineer (Bengaluru)
🏢 Impelsys
📍 Bengaluru