By Career Board
December 14, 2025
Are you tired of "Data Engineer" roles that are actually just fancy titles for manual data entry or basic Excel work? Are you a developer who loves building the pipelines that make data move rather than just staring at the final dashboard?
Barclays is hiring a Data Engineer in Pune, and this is a serious role for serious techies. This isn't just about writing a few SQL queries. It’s about building the digital backbone of a global financial giant. You will be designing data lakes, automating workflows with Python and SSIS, and preparing the ground for Machine Learning models.
If you want to move away from service-based "ticket closing" jobs and move into a high-impact Product/Bank engineering role where your code handles millions of transactions, this is your shot. We have broken down the syllabus, the interview questions, and the strategy to crack this specific role below.
✅ You Will Be Building the "Plumbing" for AI
Many companies talk about AI, but few have the data infrastructure to support it. This job description explicitly mentions "Collaboration with data scientists to build and deploy machine learning models." This means you aren't just a backend guy; you are the person who makes AI possible. You will build the pipelines that feed clean, high-velocity data to the ML algorithms. This is the most future-proof skill set you can have right now.
✅ Master the "Microsoft Stack" at Enterprise Scale
Barclays is heavily invested in the Microsoft ecosystem. By working here, you will master SQL Server and SSIS (SQL Server Integration Services) at a scale you simply cannot simulate at home. We are talking about terabytes of financial data. Becoming an expert in these tools at a bank like Barclays makes you incredibly valuable to other top-tier banks (JPMC, Morgan Stanley, Citi), ensuring your salary growth for the next decade.
✅ A Clear Path to Leadership
The JD mentions "People Leaders" and the "LEAD behaviours." Unlike many flat organizations where you stay a Senior Engineer forever, Barclays has a structured hierarchy. This role expects you to eventually "guide and persuade team members." It’s a perfect mix of hands-on coding today and team management tomorrow, giving you a clear career ladder.
Category | Details |
Role | Data Engineer |
Location | Pune, Maharashtra |
Tech Stack | Microsoft SQL, SSIS, Python |
Experience | Mid-Level (Implied by "lead/supervise" and "in-depth knowledge") |
Domain | Banking / Identity & Access Management (IAM - Preferred) |
What You Will Actually Do:
You are the architect of data movement.
The Builder: You will write Python scripts and SSIS packages to extract data from various banking systems (ATMs, Loan processing, Mobile apps).
The Guardian: You will ensure this data lands in a Data Warehouse or Data Lake without getting corrupted. Accuracy is non-negotiable in banking.
The Automator: You won't run scripts manually. You will likely use tools like Autosys (mentioned in JD) to schedule these jobs to run automatically at 2 AM while you sleep.
How You Can Succeed in the First 90 Days:
Month 1: Focus on the Schema. Understand Barclays' specific table structures. Financial databases are complex spiderwebs of relationships. Learn how the "Customer" table links to the "Transaction" table.
Month 2: Master SSIS. If you only know basic ETL (Extract, Transform, Load), you will struggle. Learn how to handle error rows and how to optimize slow-running packages.
Month 3: Start automating. If you see a team member manually running a query every morning, write a Python script to do it for them. This "Efficiency" is exactly what the "Barclays Mindset" (Empower, Challenge, Drive) is looking for.
Why This Role is a Stepping Stone:
Data Engineering is currently the hottest job in tech, often paying more than Data Science. Why? Because you can't have Data Science without Data Engineering. A couple of years at Barclays proves you can handle sensitive, high-volume, regulated data. This is the "Gold Standard" for recruiters at FAANG and FinTech companies.
Barclays interviews are technical but also focus heavily on "Values."
Where to Practice :
SQL: Go to LeetCode and filter for "Database" problems. Practice "Medium" and "Hard" questions. Focus on Joins, Window Functions (RANK, LEAD, LAG), and Common Table Expressions (CTEs).
Python: Practice string manipulation and file handling (reading CSV/JSON) on HackerRank. You don't need to know complex competitive programming algorithms, but you must know how to clean data using Pandas.
Concept 1: SSIS (SQL Server Integration Services)
Focus: Control Flow, Data Flow, ETL operations, and Package Deployment.
📺 Master Class Video: SQL Server Integration Services (SSIS) Part 1 - Getting Started
WiseOwl is the gold standard for Microsoft training. This video (and the playlist) breaks down the interface cleanly, distinguishing between "Control Flow" (the workflow) and "Data Flow" (the actual data movement), which is the first question you'll get in an SSIS interview.
Concept 2: Python for Data Engineering (Pandas)
Focus: Reading CSVs, DataFrames, Cleaning Data (dropping nulls), and Exporting to SQL.
📺 Master Class Video: Python Pandas Tutorial (Part 1): Getting Started with Data Analysis
Corey Schafer's tutorials are legendary for their clarity. He doesn't waste time on theory; he jumps straight into code. This video teaches you how to load a dataset and view it, which is the foundation for any data cleaning task you'll face in a technical test.
Concept 3: Data Warehousing Concepts (Star vs. Snowflake Schema)
Focus: Fact Tables vs. Dimension Tables, Schema Design, and Normalization.
📺 Master Class Video: Understanding Schemas in Datawarehousing | Edureka
You specifically need to know why we use a Star Schema (performance) vs. a Snowflake Schema (space). This video visualizes the relationships between Fact and Dimension tables, helping you explain "joins" and "primary keys" during the architectural design portion of the interview.
Concept 4: Autosys (Job Scheduling)
Focus: JIL (Job Information Language), Job Dependencies, and Scheduling Logic.
📺 Master Class Video: AutoSys: Working with Job Definitions Using JIL & Web UI
Autosys content is rare. This video is crucial because it covers JIL, the scripting language used to define jobs. Knowing how to read a JIL script (e.g., insert_job: job_name) is often the "Good to have" skill that separates senior candidates from juniors.
Concept 5: IAM (Identity and Access Management)
Focus: Authentication (Who are you?) vs. Authorization (What can you do?), AAA Framework.
📺 Master Class Video: What is AAA (Authentication, Authorisation, & Accounting) & IAM?
In banking, security is paramount. This video clearly differentiates between Authentication (logging in) and Authorization (permissions), a distinction you must be able to articulate when discussing how you access sensitive financial data.
❓ SQL: "Write a query to find the top 3 highest salaries in each department." (Hint: Use DENSE_RANK()).
❓ SQL: "What is the difference between DELETE and TRUNCATE? Which one can be rolled back?"
❓ SSIS: "How do you handle errors in an SSIS package? If a row fails, how do you redirect it to an error table?"
❓ Python: "How would you handle a dataset that is too large to fit in memory (RAM)?" (Hint: Chucking or processing in batches).
❓ Architecture: "Explain the difference between a Data Lake and a Data Warehouse."
❓ Barclays Value: "Tell me about a time you noticed a risk in a process and how you fixed it." (Focus on the 'Stewardship' value).
Legacy Meets Innovation
Barclays isn't just a bank; it's a 300-year-old institution that is aggressively modernizing. Working here gives you the stability of a massive corporation combined with the budget to use the latest tech. You aren't worrying about the company running out of cash next month.
The "Pune Campus" Culture
Barclays has a massive presence in Pune. It’s not a small satellite office; it’s a major technology hub. This means you have a huge community of developers, internal hackathons, and plenty of opportunities to network without ever leaving the building.
Commitment to Diversity & Inclusion
The JD highlights their strong stance on equal opportunity. Whether you are a veteran, have a disability, or come from a different background, Barclays has specific programs (like "Reach" or "Spectrum") to support you. It’s a workplace that genuinely values who you are, not just what code you write.
Q: Do I need to know Cloud (AWS/Azure) to apply?
A: The JD says it is "Good to have." If you are strong in SQL and Python, you can still get the job. However, having a basic AWS Cloud Practitioner or Azure Fundamentals certification will help your resume stand out.
Q: Is this a developer role or a support role?
A: This is primarily an Engineering/Developer role. You are building pipelines. However, "Accountabilities" mention maintenance, so expect some operational support (fixing things when they break).
Q: What is the salary range?
A: While not disclosed, Data Engineer roles at top banks in Pune for mid-level experience typically range from ₹12 LPA to ₹25 LPA, depending heavily on your interview performance and previous package.
🔥 Urgent Notice: Banking roles have strict headcount limits. Once they find a candidate, they close the portal. Don't wait.
👉 APPLY NOW: Official Link
📢 Pro Tip: "Update your LinkedIn headline to: 'Data Engineer | SQL & Python Specialist | ETL Developer' before applying. Recruiters search for these exact terms!"
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