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.

We are seeking a highly motivated and technically strong professional to play a pivotal role in our Ab Initio Modernization Programme, driving the transformation of critical data processing workloads, integration pipelines, and enterprise data assets from legacy Ab Initio-based platforms to next-generation cloud ecosystems leveraging AWS, Databricks, Spark, and modern Data Engineering frameworks.

This position offers a unique opportunity to influence strategic technology decisions, lead modernization initiatives, build migration accelerators, mentor engineering teams, and help define the target-state cloud data architecture for the organization.

The role will be instrumental in reducing dependency on legacy ETL platforms while accelerating cloud adoption, improving operational efficiency, and enabling scalable, future-ready data processing capabilities.

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

• Proven experience in Ab Initio development, architecture, and enterprise-scale implementations.
• Strong understanding of Ab Initio graphs, Co>Operating System, EME, metadata management, scheduling, and performance optimization.
• Experience assessing legacy Ab Initio workloads, dependencies, and integration frameworks.
• Hands-on experience in defining and executing modernization and migration strategies from Ab Initio to cloud-native technologies.
• Ability to perform impact assessments, identify modernization opportunities, and develop migration roadmaps.
• Experience building reusable migration frameworks, code conversion accelerators, and automation solutions Experience working with large-scale enterprise data warehouses and data integration solutions.
• Strong ETL/ELT design and development expertise.
• Advanced SQL skills across Teradata, Hadoop, and enterprise database platforms.
• Experience designing and developing large-scale data integration and data transformation solutions.
• Deep understanding of data warehousing, dimensional modeling, data lakes, and modern lakehouse architecture.
• Experience handling large-scale enterprise datasets with strong focus on performance, scalability, and reliability
• Experience modernizing and migrating legacy workloads to cloud-based platforms.
• Strong understanding of cloud-native data engineering patterns.
• Experience designing scalable data pipelines using AWS services and modern data processing frameworks.
• Ability to define target-state architectures that improve agility, maintainability, and operational efficiency.
• Demonstrated ability to lead technical transformation initiatives from concept through production delivery.
• Capability to drive proof-of-concepts, technology evaluations, and modernization accelerators.
• Experience influencing engineering, architecture, and business stakeholders.
• Strong analytical and problem-solving skills with a continuous improvement mindset.
• Ability to mentor junior engineers and establish engineering best practices.
• Ability to work closely with business, architecture, platform, and delivery teams.
• Strong communication skills to translate technical decisions into business outcomes.
• Experience leading cross-functional discussions and driving alignment on modernization strategies. Proven ability to operate effectively within Agile delivery environments.

Some of Highly Valued Skills may include:

• Amazon S3.
• AWS Glue.
• AWS Lambda.
• AWS EMR.
• Amazon Redshift.
• IAM and Security Controls.
• AWS Data Migration Services.
• Cloud-native Data Engineering Patterns.
• Snowflake architecture and virtual warehouses.
• Data sharing and secure data access.
• Performance optimization concepts.
• Data loading and ingestion patterns.
• Cost and storage optimization fundamentals.
• Databricks Lakehouse architecture.
• Delta Lake concepts. Databricks Lakehouse Architecture.
• Apache Spark.
• PySpark Development.
• Delta Lake.
• Unity Catalog.
• Performance Optimization Techniques.
• Notebook-Based Development.
• Batch and Streaming Data Processing.
• Cloud-Native Analytics Platforms.
• ETL Conversion Frameworks.
• Metadata-Driven Solutions.
• Data Lineage and Impact Analysis.
• Automated Code Conversion Approaches.
• Modern ETL/ELT Tools (DBT, Glue, Spark).
• Enterprise Migration Programmes.

You may be assessed on the 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 location of the role is Pune, IN.