Data Engineer

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 meet the needs of stakeholders/ customers through specialist advice and support
• Perform prescribed activities in a timely manner and to a high standard which will impact both the role itself and surrounding roles.
• Likely to have responsibility for specific processes within a team
• They may lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. They supervise a team, allocate work requirements and coordinate 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 manage own workload, take responsibility for the implementation of systems and processes within own work area and participate on projects broader than direct team.
• Execute work requirements as identified in processes and procedures, collaborating with and impacting on the work of closely related teams.
• Check work of colleagues within team to meet internal and stakeholder requirements.
• Provide specialist advice and support pertaining to own work area.
• 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 all teams in area contribute to the objectives of the broader sub-function, delivering impact on the work of collaborating teams.
• Continually develop awareness of the underlying principles and concepts on which the work within the area of responsibility is based, building upon administrative / operational expertise.
• Make judgements based on practise and previous experience.
• Assess the validity and applicability of previous or similar experiences and evaluate options under circumstances that are not covered by procedures.
• Communicate sensitive or difficult information to customers in areas related specifically to customer advice or day to day administrative requirements.
• Build relationships with stakeholders/ customers to identify and address their needs.

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 infrastructure and deployment pipelines, driving innovation and operational excellence. You will harness cutting-edge technology to build and manage robust, scalable and secure infrastructure, ensuring seamless delivery of our digital solutions. 

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

• Hands on experience in pyspark and strong knowledge on Dataframes, RDD and SparkSQL.

• Hands on Experience in developing, testing and maintaining applications on AWS Cloud.

• Strong hold on AWS Data Analytics Technology Stack (Glue, S3, Lambda, Lake formation, Athena).

• Design and implement scalable and efficient data transformation/storage solutions using Snowflake.

• Experience in Data ingestion to Snowflake for different storage format such Parquet, Iceberg, JSON, CSV etc.

• Experience in using DBT (Data Build Tool) with snowflake for ELT pipeline development.

• Experience in Writing advanced SQL and PL SQL programs.

• Hands On Experience for building reusable components using Snowflake and AWS Tools/Technology.

• Should have worked at least on two major project implementations.

• Exposure to data governance or lineage tools such as Immuta and Alation is added advantage.

• Experience in using Orchestration tools such as Apache Airflow or Snowflake Tasks is added advantage.

• Knowledge on Abinitio ETL tool is a plus.

Some other highly valued skills may include:

• Ability to engage with Stakeholders, elicit requirements/ user stories and translate requirements into ETL components.

• Ability to understand the infrastructure setup and be able to provide solutions either individually or working with teams.

• Good knowledge of Data Marts and Data Warehousing concepts.

• Resource should possess good analytical and Interpersonal skills.

• Implement Cloud based Enterprise data warehouse with multiple data platform along with Snowflake and NoSQL environment to build data movement strategy.

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 Chennai.