Data Engineer

Role & Responsibilities:

Responsibilities

• Design and develop scalable ETL/ELT data pipelines using Python, PySpark, MSBI and Apache Spark.
• Build and manage lake house/data platforms, including data modelling, partitioning, metadata and Iceberg tables.
• Deploy and manage data pipelines using Kubernetes, Docker, CI/CD and DevOps practices in on-premise environments.
• Provide L3 support, optimise data platform performance, ensure security/governance and collaborate with technical and business stakeholders.

Requirements

• Demonstrated experience in data engineering/pipeline development, with strong Python, SQL Server and MSBI expertise.
• Hands-on experience with Kubernetes, Docker, Apache Spark/PySpark and Apache Airflow for data processing and orchestration.
• Strong data modelling skills across relational and NoSQL databases, including MongoDB or Cassandra.
• Experience with lakehouse/data lake architecture, Iceberg, partitioning, metadata management, CI/CD, Git and IaC.
• Strong understanding of data security, governance, RBAC and data masking.

Next Step:

If interested, you can click on “Apply here” or write an e-mail to [email protected] with your updated resume.

NOTE: - Only shortlisted candidates will be contacted back.

Thanks & Regards

Deeksha Agarwal

EA Licence No.91C2918

Personnel Registration No. R26161520