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.

Analyst Expectations

• To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
• Requires in-depth technical knowledge and experience in their assigned area of expertise
• Thorough understanding of the underlying principles and concepts within the area of expertise
• They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
• 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 develop technical expertise in work area, acting as an advisor where appropriate.
• Will have an impact on the work of related teams within the area.
• Partner with other functions and business areas.
• Takes responsibility for end results of a team’s operational processing and activities.
• Escalate breaches of policies / procedure appropriately.
• Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
• Advise and influence decision making within own area of expertise.
• Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
• Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
• Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Make evaluative judgements based on the analysis of factual information, paying attention to detail.
• Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
• Guide and persuade team members and communicate complex / sensitive information.
• Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.

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 take part in the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unparalleled customer experiences. As a part of the team, you will deliver technology stack, using strong analytical and problem solving skills to understand the business requirements and deliver quality solutions. You'll be working on complex technical problems that will involve detailed analytical skills and analysis. This will be done in conjunction with fellow engineers, business analysts and business stakeholders. 
 
To be successful as a Data Engineer you should have experience with:

• Strong experience with ETL tools such as Ab Initio, Glue, PySpark, Python, DBT, DataBricks and various AWS required services / products.
• Advanced SQL knowledge across multiple database platforms (Teradata , Hadoop, SQL etc.)
• Experience with data warehousing concepts and dimensional modeling.
• Proficiency in scripting languages (Python, Perl, Shell scripting) for automation.
• Knowledge of big data technologies (Hadoop, Spark, Hive) is highly desirable.
• Bachelor's degree in Computer Science, Information Systems, or related field.
• Experience in ETL development and data integration.
• Proven track record of implementing complex ETL solutions in enterprise environments.
• Experience with data quality monitoring and implementing data governance practices.
• Knowledge of cloud data platforms (AWS, Azure, GCP) and their ETL services.

Some other highly valued skills include:

• Strong analytical and problem-solving skills.
• Ability to work with large and complex datasets.
• Excellent documentation skills.
• Attention to detail and commitment to data quality.
• Ability to work independently and as part of a team.
• Strong communication skills to explain technical concepts to non-technical stakeholders.

 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 in Pune.