*hackajob
is collaborating with
Barclays
to connect them with exceptional professionals for this role.*
Join us as a Data Engineer - SQL, Snowflake at Barclays, responsible for supporting the successful delivery of location strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences.

To be successful as a Data Engineer - SQL, Snowflake you should have experience with:
- SQL – Advanced query writing and performance tuning.
- Teradata – Experience with enterprise data warehousing.
- PySpark – Proficiency in distributed data processing.
- Hadoop – Familiarity with big data tools and architecture.
- Linux Shell Scripting – Solid scripting skills for automation and data handling.

Some Other Highly Valued Skills May Include
- AWS Awareness – Understanding of cloud-based data platforms and services.




- Prior Exposure to AWS – Experience with data migration or analytics on AWS is a strong plus.

You may be assessed on 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 out of Pune.

Purpose of 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.

Accountabilities
- 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 th

📌 Data Engineer (Pune Division)
🏢 hackajob
📍 Pune Division