Data Engineer Lead

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 an adequately skilled and highly motivated Data Engineer to design, build, and maintain scalable and efficient data pipelines while collaborating with cross-functional teams to deliver high-quality, actionable regulatory data solutions as well as insightful business analytics. 

You may be assessed on the key critical skills relevant for success in role, such as hands-on and strong modern data stack experiences in Python, SQL, DBT, AWS, S3 storage, Databricks or Snowflake. 

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

• Building scalable and efficient ETL/ELT pipelines to ingest, transform, and load data for Reg reporting / analytical use cases. 

• Optimize Performance: Tune and optimize data pipelines, SQL queries, and data models for performance and scalability. 

• Python Proficiency for data manipulation, integration and with Pandas or PySpark experience. 

• Strong SQL skills for complex queries & experience with database platforms. 

• Hands-on experience building and managing DBT models & with DBT Cloud or DBT core. 

• Experience building and managing the object store. 

• Experience with AWS services for data engineering (e.g., S3, Glue, Lambda, Redshift). 

• Utilize Starburst, Databricks or Snowflake for big data processing and advanced analytics.   

• Partner with project managers, data analysts, data scientists, and business stakeholders to deliver end-to-end data solutions.       

• Develop monitoring and validation routines to ensure data accuracy, consistency, and security.  

• Work closely with data architect and data modelers/ analysts to design and implement data models that support business intelligence and analytics. 

Desirable skillsets / good to have: 

• Familiarity with Databricks or Snowflake for big data processing and analytics is a plus. 

• Proficient with Git for version control and collaboration. 

• Familiarity with tools like Airflow, Dagster, or similar workflow automation platforms. 

• Experience in working with RESTful or GraphQL APIs for data integration. 

• Strong problem-solving and analytical skills with a focus on delivering high quality data solutions. 

• Excellent communication and collaboration skills to work with cross-functional teams. 

• Ability to adapt to a fast-paced and dynamic environment. 

• Self-motivated, detail-oriented, and passionate about data engineering. 

This role will be based out of Nirlon Knowledge Park / Altimus office, Mumbai.