Data Analyst

Barclays' interview process typically starts with a timed online assessment that tests quantitative aptitude and SQL fundamentals. Successful candidates move to a technical interview where they discuss data modeling, data quality frameworks, and solve case‑based problems. The final HR round assesses cultural fit, communication skills, and motivation. Preparation should focus on clear articulation of past projects and a solid grasp of data governance concepts.

Barclays promotes a collaborative culture where innovation and continuous learning are encouraged. Employees benefit from structured mentorship, clear career progression, and a healthy work‑life balance supported by flexible working policies.

Graduates (B.Tech/B.E., B.Sc., M.Tech, MSc) in Computer Science, Information Technology, Statistics, Mathematics, Economics or related fields; Minimum 60% aggregate (or CGPA 6.0/10); No active backlogs; Batch 2025‑2027; Strong analytical mindset and willingness to learn.

Round 1: Online Assessment (aptitude + SQL) → Round 2: Technical Interview (data concepts, problem solving) → Round 3: HR Interview (fit & motivation)

Barclays is a global financial services powerhouse with a heritage spanning over three centuries. In India, the bank has built a strong presence across retail, corporate, and investment banking, emphasizing digital transformation and data‑driven decision making. The Corporate Digital Banking division in Pune focuses on delivering innovative, technology‑enabled solutions to large enterprise clients, helping them streamline cash management, trade finance, and treasury operations. As part of its Data & Analytics function, Barclays invests heavily in modern data architectures, data‑as‑a‑product thinking, and robust governance frameworks to stay ahead in a competitive market. The Data Analyst role is a permanent position that sits at the heart of the data ecosystem for Corporate Digital Banking. The analyst will partner with business stakeholders, data engineers, and product owners to ensure that data is accurate, reliable, and readily consumable for analytics and reporting. The role blends investigative work—tracing data lineage, resolving quality issues, and documenting sources—with hands‑on development of pipelines, dashboards, and logical data models. Candidates will get exposure to cutting‑edge data virtualization platforms and will contribute to the bank’s broader data mesh strategy. Key responsibilities include: 1. Investigate and resolve data quality, lineage, and source‑identification issues across multiple banking systems. 2. Document data sources, transformation logic, and create comprehensive source‑to‑target mapping documents. 3. Design, develop, and maintain automated data pipelines for seamless data movement and processing. 4. Perform exploratory data analysis on large datasets to uncover trends, anomalies, and actionable insights. 5. Build logical and physical data models that support reporting and analytical use cases. 6. Develop interactive dashboards and visual reports using tools such as Tableau or Power BI, catering to both technical and non‑technical stakeholders. 7. Automate recurring reporting workflows to improve efficiency and reduce manual effort. 8. Collaborate with data governance teams to enforce data standards, metadata management, and compliance requirements. 9. Participate in data integration initiatives, ensuring seamless ingestion from legacy and cloud‑based sources. 10. Stay updated with emerging data technologies, data‑as‑product concepts, and best practices in data mesh architecture. The tech stack typically includes SQL, Python or R for scripting, data virtualization platforms (e.g., Denodo), ETL tools, cloud services (AWS/GCP), and visualization tools like Tableau or Power BI. Barclays offers a clear growth path: junior analysts can progress to senior analyst, data engineer, or analytics manager roles, with opportunities to move across domains or geographies. Joining Barclays means working in a collaborative, inclusive environment that values continuous learning, offers mentorship programs, and provides exposure to global banking challenges—making it an ideal launchpad for fresh graduates eager to build a career in data analytics.