Data Engineer - ETL

Job description

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 - ETL at Barclays, responsible for supporting the successful delivery of location strategy projects to plan, budget, agreed quality and governance standards. You will be invoved in design, develop, and deliver scalable data solutions. The successful candidate will be responsible for building robust data pipelines, enabling data processing and supporting large-scale data transformation initiatives across the organisation. This role requires strong expertise in PySpark, AWS cloud technologies, data engineering practices and modern data platform architectures. The candidate will collaborate with business stakeholders, architects, product owners and engineering teams to deliver secure, reliable and performant data products. To be successful as a Data Engineer - ETL you should have experience with: Design, develop and maintain scalable data pipelines using PySpark. Build and optimise ETL/ELT solutions supporting large-scale enterprise data processing requirements. Develop reusable frameworks, components and standards to accelerate data onboarding and analytics delivery. Implement data quality controls, validation frameworks and reconciliation processes. Deliver high-quality code following engineering best practices, coding standards and automated testing approaches. Some other highly valued skills may include: Excellent programming skills in Python/Pyspark. Hands-on experience with Databricks and/or Snowflake. Strong experience with AWS Cloud services including S3, Glue, EMR, Lambda, EC2, DynamoDB, IAM, CloudWatch and CloudTrail. Hands-on experience developing and optimising AWS Glue ETL jobs using PySpark. Experience with large-scale distributed data processing. Solid understanding of Data Lake, Lakehouse and Modern Data Platform architectures. Expertise with Git-based source control platforms. Experience in Airflow. 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 Bengaluru.