Data Analyst Job Openings in Pune 2026!!!
Barclays announced job vacancy for the post of Data Analyst.The place of posting will be at Pune.Candidates who have completed Graduate / Engineering / Post Graduate with Fresher / Experience are eligible to apply. More details about qualifications, job description and roles & responsibilities are as follows
Company Overview
| Name of the Company | Barclays |
| Required Qualifications | Graduate |
| Skills | Using programming tools like Python or R for deeper analysis |
| Category | Data & Analytics |
| Work Type | Onsite |
Join them as a Data Analyst 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 their digital solutions.
Job Details
Θ Positions: Data Analyst
Θ Job Location: Pune
Θ Salary: As per company standards
Θ Job Type: Full Time
Θ Requisition ID: JR-0000089713
Roles and Responsibilities:
- To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.
- Accountabilities
- Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement.
- Designing and building data pipelines to automate data movement and processing.
- Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI.
- Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements.
- Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.
- 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.
Required Skills & Qualifications:
- Delivery of analytical outputs that convert complex data into clear insight, recommendations, and measurable business value.
- Cleaning and preparing data with accuracy
- Using Excel and spreadsheets to organize and study information
- Working with SQL to manage and query databases
- Applying statistical methods to understand patterns
- Creating clear visuals and explaining insights in a simple way
- Using programming tools like Python or R for deeper analysis
- Partner with business, technology, risk, finance, operations, and data teams to define analytical requirements, success measures, and data-driven solutions.
- Design, enhance, and govern dashboards, reports, scorecards, and analytical frameworks that support performance management, operational oversight, risk mitigation, and strategic initiatives.
- Conduct deep-dive analysis to identify trends, anomalies, root causes, opportunities, and risks, translating findings into clear narratives for senior stakeholders.
- Ensure analytical outputs are accurate, complete, controlled, and aligned with data quality, data governance, privacy, security, and regulatory expectations.
- Provide subject matter expertise on data interpretation, metric definition, business logic, and analytical best practice across the function.
- Drive continuous improvement by identifying opportunities to simplify reporting, automate manual analysis, improve data quality, and enhance stakeholder self-service capability.
Some other highly valued skills may include:
- Deliver high-quality analytical work in a timely manner, consistently applying sound judgement, attention to detail, and a continuous improvement mindset.
- Demonstrate strong technical and business knowledge across data analysis, reporting, visualisation, data quality, metric design, and business performance interpretation.
- Understand the underlying principles, concepts, and drivers within the relevant business area and use this knowledge to shape insight, challenge assumptions, and influence outcomes.
- Lead analytical workstreams or small teams where required, guiding priorities, reviewing outputs, supporting professional development, and ensuring delivery against agreed objectives.
- 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.
- For an individual contributor role, act as a trusted advisor in the data analytics domain, developing specialist expertise and providing guidance to stakeholders and colleagues.
- Have an impact on the work of related teams by improving insight, strengthening decision-making, and supporting the delivery of functional and organisational objectives.
- Partner with other functions and business areas to understand priorities, clarify problems, align definitions, and deliver analytics that support enterprise-wide outcomes.
- Take responsibility for the end-to-end quality of analytical deliverables, including requirements capture, data sourcing, validation, interpretation, presentation, and stakeholder sign-off.
- Escalate breaches of policies, procedures, data quality standards, controls, or regulatory expectations appropriately and in a timely manner.
- Take responsibility for embedding new policies, procedures, controls, and analytical standards adopted due to risk mitigation or regulatory requirements.
- Advise and influence decision-making within own area of expertise by presenting clear evidence, options, trade-offs, and recommendations.
- Take ownership for managing risk and strengthening controls in relation to the work owned or contributed to. Deliver work and areas of responsibility in line with relevant rules, regulations, standards, and codes of conduct.
- Maintain and continually build an understanding of how the sub-function integrates with the wider function, alongside knowledge of the organisation’s products, services, data landscape, processes, and control environment.
- Demonstrate understanding of how analytical outputs coordinate with and contribute to the achievement of organisational and sub-functional objectives.
- Make evaluative judgements based on factual information, analytical evidence, business context, and appropriate challenge of data limitations or assumptions.
- Resolve problems by identifying and selecting solutions through the application of analytical expertise, business understanding, and precedent, while escalating complex or material issues as required.
- Guide and persuade team members and stakeholders, communicating complex, sensitive, or technical information in a clear and accessible way for different audiences.
- Act as a contact point for stakeholders outside the immediate function, building a strong network of contacts across teams and, where appropriate, external to the organisation.
- Promote responsible data usage, effective documentation, reproducible analysis, and a culture of insight-led decision-making across the team.
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