Data Engineer

Job Description

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.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L - Listen and be authentic, E - Energise and inspire, A - Align across the enterprise, D - Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

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'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.

You may be assessed on the key critical skills relevant for success in role, such as experience with, skills to meet business requirement as well as job-specific skillsets.

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

Essential Skills

• Design, develop, and maintain scalable ETL/ELT data pipelines in cloud environments.
• Build and optimize data ingestion frameworks from various sources (APIs, databases, streaming).
• Implement data transformation logic using modern data engineering tools.
• Develop and maintain data quality frameworks and monitoring solutions.
• Optimize data pipeline performance and reduce infrastructure costs.
• Implement CI/CD practices for data pipeline deployment.
• Troubleshoot and resolve data pipeline issues and performance bottlenecks.
• Document data flows, pipeline architecture, and operational procedures.
• Ensure data security and compliance with regulatory requirements.
• Proficiency in SQL and database technologies (relational and NoSQL).

Some other highly valued skills include:

• Strong programming skills in Python, Scala, or Java.
• Work with Data Scientists and Analysts to ensure data availability and quality.
• Experience with modern data platforms (Databricks, Snowflake, Spark).
• Experience with streaming technologies (Kafka, Kinesis, Event Hubs).
• Knowledge of containerization (Docker, Kubernetes) and orchestration tools (Airflow, Dagster).
• Understanding of data warehousing concepts and dimensional modelling
• Experience with version control (Git) and CI/CD pipelines.
• Experience in cloud data services (AWS Glue, Azure Data Factory, GCP Dataflow).

This role is based out of Pune.