Data Engineer
Barclays · Pune · Posted 2026-07-23
Tech stack: AWS, Python
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About the role
To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.
Responsibilities:
- Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
- Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
- Development of processing and analysis algorithms fit for the intended data complexity and volumes.
- Collaboration with data scientist to build and deploy machine learning models.
Qualifications:
- Strong AWS Services, Glue, Lambda, S3, Athena skills
- ETL and Databases Concepts,
- Python and Pyspark experience is a must
- Experience with Git Hub , Data Modeling , Software Designing, Understand ETL tools such as Abinitio and ETL frameworks
- Strong communication skills and Private banking experience.
- You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.
- This role is based in Pune.
Qualifications
- Strong AWS Services, Glue, Lambda, S3, Athena skills
- ETL and Databases Concepts
- Python and Pyspark experience is a must
- Experience with Git Hub, Data Modeling, Software Designing, Understand ETL tools such as Abinitio and ETL frameworks
- Strong communication skills and Private banking experience.
- You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.
- This role is based in Pune.
Responsibilities
- Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
- Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
- Development of processing and analysis algorithms fit for the intended data complexity and volumes.
- Collaboration with data scientist to build and deploy machine learning models.