AVP Data Analyst at Barclays

, , India -

Full Time

Start Date

Immediate

Expiry Date

07 Mar, 26

Salary

0.0

Posted On

07 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Quality, Data Cleansing, Data Transformation, Data Pipelines, Machine Learning, AI, SQL, Python, Agile, Stakeholder Management, Risk Management, Change Delivery, Project Management, Data Governance, Analytical Techniques, Documentation

Industry

Banking

Description

Job Description 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 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. Join us as an "AVP Data Analyst" at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. To be successful as an "AVP Data Analyst", you should have experience with: Data and Record Governance experience. Change Delivery. Project Management. SQL, Python or Lead Developer Experience. Some other highly valued skills may include (Mandatory): Agile experience. Stakeholder management. Location-Chennai. 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. Our Work Experience is the combination of everything that's unique about us: our culture, our core values, our company meetings, our commitment to sustainability, our recognition programs, but most importantly, it's our people. Our employees are self-disciplined, hard working, curious, trustworthy, humble, and truthful. They make choices according to what is best for the team, they live for opportunities to collaborate and make a difference, and they make us the #1 Top Workplace in the area.

Responsibilities

The AVP Data Analyst will implement data quality processes and procedures, ensuring data reliability and extracting actionable insights to improve operations. Responsibilities include investigating data issues, executing data cleansing tasks, and developing advanced analytical techniques to solve complex business problems.