AVP - Data Analyst

Noida, Uttar Pradesh

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Date live: Aug. 07, 2025

Business Area: Wholesale Onboarding and Group FCO

Area of Expertise: Data & Analytics

Reference Code: JR-0000045958

Contract: Permanent

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Join us as Assistant Vice President – Data Analyst, for the Financial Crime Operations Data Domain to implement data quality process and procedures in a complex landscape where the data flows from multiple systems & models which involves Transaction source systems, payment applications, screening & filtering applications, case management systems, Machine Learning Model/APIs and reporting systems/DWH.

The Data Analyst job primarily involves ensuring that data is reliable and trustworthy, then extract actionable insights from it to help the organization improve its operation and optimize resources.

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 using ETL tools like Python
Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems. (will involve advanced understanding and experience in Python, SQL and other data handling skills)
Documentation of data quality findings and recommendations for improvement.
Set up mechanism for proactive monitoring of data quality

To be successful in this role, you should have:

Experience in Data Management, Data Governance including records management. Ability to review business processes from data lens and identify critical upstream and downstream components especially in financial services organisation – understanding of models, EUDAs etc.
Strong understanding of Data Governance, Data Quality & Controls, Data Lineage and Reference Data/Metadata Management including relevant policies and frameworks
A clear understanding of the elements of an effective control environment, enterprise risk management framework, operational risk or other principal risk frameworks
Experience of managing stakeholders directly & indirectly and across geographies & cultures.
Strong understanding and practical exposure to application of BCBS 239 principles and related frameworks
Commercially astute, demonstrates a consultative, yet pragmatic approach with integrity to solving issues, focusing on areas of significance and value to the business.
A strong understanding of Risk and Control environment/control frameworks/op risk, including understanding of second and third line functions and impact across people, process and technology.
Analytical techniques and tools to extract meaningful insights from complex data sets and drive data- Strategic Leadership: Provide strategic direction and leadership for data analysis initiatives, ensuring alignment with organizational and program goals. Functional understanding of financial crime and fraud data domains would be preferred.
Data Governance: Oversee data governance policies and procedures to ensure data integrity, security, and compliance with regulatory requirements.
Stakeholder Collaboration: Collaborate with cross-functional teams to identify data needs and deliver actionable insights.
Advanced Analytics: Utilize advanced driven decision-making
Deliver best in class insights to enable stakeholders to make informed business decisions and support data quality issue remediation.
Perform robust review and QA of key deliverables being sent out by the team to stakeholders.
Demonstrate a collaborative communication style, promoting trust and respect with a range of stakeholders including Operational Risk/Chief Controls Office/ Chief Data Office/ Financial Crime Operations subject matter experts (SMEs), Chief Data Office, Risk Information Services, Technology.

Some other desired skills include:

Graduate in any discipline.
Effective communication and presentation skills.
Experience in Data Management/ Data Governance/ Data Quality Controls, Governance, Reporting and Risk Management preferably in a financial services organisation
Experience in Data Analytics and Insights (using latest tools and techniques e.g. Python -mandatory and Tableau, Tableau Prep, Power Apps, Aletryx good to have), analytics on structured and unstructured data.
Experience on data bases and data science/ analytics tools and techniques like SQL, AI and ML (on live projects and not just academic projects).
Proficient in MS Office – PPT, Excel, Word & Visio.
Comprehensive understanding of Risk, Governance and Control Frameworks and Processes.

Location-The location is based out of Noida.

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.

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.

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.