Data Engineer Job Openings At Barclays – Apply Now!

Qualifications

To be successful as a Data Engineer you should have experience with:

• Programming experience in Java or Python.
• Knowledge of RDBS/NoSQL databases and Data Ware house concepts.
• Familiarity with AWS Services (Glue, Redshift, Lambda etc.).
• Familiarity with  batch process, Stream Processing and data integration techniques using big data framework Spark.

Some other highly valued skills may include:

• Knowledge of data visualization tools like Tableau, SAP BO.
• Experience in containerization using docker and Kubernetes.
• Familiarity with Serverless computing platform.

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.

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 the intended data complexity and volumes.
• Collaboration with data scientist to build and deploy machine learning models.