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
Assistant Vice President Expectations
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Join us as a Data Engineer at Barclays, where you will spearhead the evolution of our data platforms and real-time processing capabilities, driving innovation and operational excellence. You will harness cutting-edge cloud and streaming technologies to build and manage scalable, resilient, and secure data solutions, enabling seamless delivery of our digital and data-driven services.
To be successful as a Data Engineer you should have experience with:
Experience in Databricks with creation of data products, pipelines, scheduling jobs, etc. in AWS.
Develop Kafka Streams, Spring Kafka, and Apache Flink applications for real-time event processing
Implement parsers for various message formats: ISO 20022 XML, SWIFT MT, JSON, and flat files
Build data transformation logic to flatten hierarchical messages into target AVRO schemas
Implement stateful transformations including aggregations, joins, and windowed operations
Integrate with source systems via IBM MQ and Kafka topics
Write clean, testable, and well-documented code following established standards
Create and maintain unit tests and integration tests for developed components
Participate in code reviews and incorporate feedback constructively
Troubleshoot issues using ELK stack and application logs
Actively participate in Scrum ceremonies and collaborate with team members
Strong proficiency and solid understanding of core concepts and modern features with cloud technologies such as Snowflake, AWS, Databricks.
Hands-on experience with Spring Boot and Spring Framework
Strong unit testing skills using JUnit 5 and Mockito
Good understanding of data structures and algorithms
Experience with Git and collaborative development workflows
Some other highly valued skills may include
Experience with IBM MQ or JMS-based messaging
Knowledge of payment processing domain and creation of Data products in a Data mesh space.
Familiarity with ELK stack for logging and troubleshooting
Experience with SWIFT parsing libraries (Prowide Core)
Experience with Flink stateful processing, checkpointing, and state backends
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.
The role is based out of Pune.
Based on 1,491 disclosed Data & ML salaries on RoleSuite, the role pays a median of $162K/year, with most offers between $127K and $203K (10th–90th percentile: $106K–$245K).
See the full Data & ML salary breakdown →