Lead / Senior Data Engineer

Impelsys; Bengaluru; Hybrid; INR 3,000,000 - 6,000,000; Full time

Job summary

Impelsys is expanding its Data & AI practice in Bengaluru, building cloud data platforms and analytics for global enterprises. You will design, build, test and run end-to-end data pipelines on AWS, migrating legacy workloads and enabling business-ready data products.

As a Senior/Lead Data Engineer, you will shape coding standards, mentor engineers and collaborate with cross-functional teams while leveraging dbt, PySpark, SQL, Airflow and modern lakehouse architectures.

Qualifications

• Proficient in Python, PySpark and SQL.
• Experience with dbt and Apache Airflow.
• AWS data stack including S3, Glue, Athena; Redshift a plus.

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 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.

Skills

Python

PySpark

SQL

dbt

Apache Airflow

AWS

Data modelling

Git

CI/CD

Data-quality testing

Job description

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 modern 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).