Data Business Analyst

Data Business Analyst at Barclays

Join us as a Data Business Analyst. At Barclays, we don’t just adapt to the future, we create it. As a Data Business Analyst, you will harness cutting-edge technology to revolutionize our digital offerings, ensuring unparalleled customer experiences.

What you'll need to succeed

To be a successful Data Business Analyst, you should have experience with:

• Hands on experience in modern data analytics platforms and reporting data warehouses.
• Deep understanding of Data warehousing principles with hands on knowledge on scalable data ingestion techniques through secure pipelines.
• Ability to perform business and data analysis alongside working with technology colleagues, developers and business stakeholders.
• Working experience on Agile methodologies like Scrum, Kanban or any other Agile framework.
• Working experience of using Python for Data Analysis & Profiling.
• Ability to translate business requirements into technical stories.
• Solid written and verbal communication skills.
• Ability to be proactive, a team player and having a ‘can-do’ attitude.

Highly Valued Additional Skills

Given below are highly valued:

• Knowledge in Retail, Investment Bank or Correspondent Banking Anti-Money Laundering (AML) Transaction Monitoring.
• Knowledge of data modelling techniques and exposure to any modelling tool preferred.
• Exposure to data controls techniques would be an added advantage.
• Knowledge and understanding of Data Analysis and Visualization tools like SQL/Tableau/Power BI, etc.
• Solid written and verbal communication skills.
• Certification in AWS, Databricks Lakehouse, DBT Fundamentals would be an added advantage.

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.

Purpose of the Role

To implement data quality process and procedures, ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organisation improve its operation, and optimise resources.

Key Accountabilities

• Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification.
• Execution of data cleansing and transformation tasks to prepare data for analysis.
• Designing and building data pipelines to automate data movement and processing.
• Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems.
• Documentation of data quality findings and recommendations for improvement.

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.
• 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.

Key skills/competency

• Data Analytics Platforms
• Data Warehousing Principles
• Secure Data Pipelines
• Business & Data Analysis
• Agile Methodologies
• Python for Data Analysis
• SQL/Tableau/Power BI
• Machine Learning & AI
• Data Quality Management
• Stakeholder Communication