S&P Global Software Engineering Intern — Chennai / Hyderabad (2026)

About the role

S&P Global's 2026 Software Engineering Internship in Chennai and Hyderabad — build the financial-technology platforms behind market intelligence, ratings and indices. Java, Python, AWS.

S&P Global's Indian engineering presence — across the Chennai (Ambit IT Park) and Hyderabad (Knowledge City and Raheja Mindspace) campuses — is one of the most under-rated technical organisations in the Indian product-company recruiting market. S&P Global is the parent of S&P Ratings, S&P Market Intelligence, S&P Dow Jones Indices and S&P Commodity Insights (formerly Platts) — collectively the firm provides the financial-data infrastructure that institutional investors, banks, asset managers and corporates rely on for credit ratings, index methodologies, market data and commodity pricing. The Indian engineering centres ship the platforms that deliver this data, and the work is genuinely substantive — high-throughput data ingestion, low-latency market-data APIs, the cloud migration of decades of legacy ratings infrastructure to AWS, and the GenAI-augmented research products that the company has been investing in since 2023. Chennai is the larger of the two centres and houses the Market Intelligence engineering organisation; Hyderabad is the home of the Ratings cloud-migration effort, parts of the Indices platform and the GenAI / Cortex AI initiative. Intern matching happens after the offer based on resume, project work and stated technical interest. Day-to-day work is structured around a clearly scoped intern project owned by the intern under a senior engineer mentor. The first two weeks are onboarding to S&P Global's internal tooling — the cloud platform (AWS, with significant on-going migration from on-premise), the proprietary financial-data domain models, the Slack workspace, and the company's specific testing and release workflow. Weeks three through ten are execution, where the intern writes Java (the dominant language for the Market Intelligence platform), Python (for the data-engineering and GenAI sub-teams) or occasionally Scala (for the Spark-heavy data pipelines). The financial-domain context is a meaningful part of the work — the intern is expected to learn enough about credit ratings, index methodology or market data to contribute substantively to the technical design conversations. The technical bar is meaningful but not as algorithmically demanding as the top-tier product-company loops. The interview process is two rounds: a 60-minute coding screen at the LeetCode-easy-to-medium level on a shared coding platform, and a project-deep-dive plus behavioural interview where the candidate walks through one of their college or personal projects in technical depth. The project round is heavily weighted; S&P Global places significant value on the candidate's ability to talk substantively about ONE project they built, including the design choices and the trade-offs considered. Candidates who can speak credibly about a Java Spring Boot project, a Python data-pipeline project or an AWS-deployed application consistently outperform candidates with thinner project portfolios. The career trajectory out of an S&P Global internship is genuinely strong for candidates interested in financial technology. The S&P Global brand on a CV is a hard-currency credential in the financial-data and fintech ecosystem; alumni at the two-year mark are heavily recruited by Bloomberg, MSCI, Moody's, FactSet, and the Indian fintech tier (Razorpay, Cred, PhonePe at the senior level). The internal trajectory is also strong — S&P Global India has been deliberately investing in the engineering organisation since the 2022 IHS Markit merger, and the promotion velocity has improved meaningfully since then. For candidates applying now, the practical priorities are: complete the application on the S&P Global Careers portal with a resume that highlights any project involving financial data (even a stock-price visualisation or a Kaggle dataset on lending counts); express the Chennai vs Hyderabad preference deliberately on the application form; and prepare for the project-deep-dive interview by writing a one-page narrative of one college or personal project — problem statement, design choices, alternatives considered, outcomes and what you would change.

Responsibilities

Own a clearly scoped intern project on the Market Intelligence, Ratings or Indices platform. Write Java (Spring Boot dominant), Python or Scala per the team. Contribute to AWS-based services, data pipelines or the GenAI / Cortex AI initiative. Participate in sprint planning, code reviews and the team's release train. Demo the project at the end-of-summer review.

Requirements & qualifications

Pursuing B.Tech / M.Tech in Computer Science, IT or related field with 2026 or 2027 graduation. Strong fundamentals in data structures and algorithms (LeetCode-easy to medium). Working knowledge of Java (Spring Boot a plus), Python or Scala. Comfortable with AWS, SQL and Git. Strong written and spoken English. One college or personal project you can speak to in depth.

Why this role in 2026

Excellent external market at Bloomberg, MSCI, Moody's and the Indian fintech tier.

Application tips

Apply via the S&P Global Careers portal. Express Chennai vs Hyderabad preference deliberately. Write a one-page project narrative — problem, design choices, alternatives, outcomes — for the project round. Reference any college project involving financial data, even a simple stock-price dashboard or a Kaggle lending dataset.

Interview preparation

Two rounds: 60-minute coding screen (LeetCode-easy to medium), project-deep-dive plus behavioural interview. The project round is heavily weighted — practise narrating ONE project end-to-end in 5 minutes covering problem, design choices, alternatives, outcome and what you would change.

Career growth

External mobility to Bloomberg, MSCI, Moody's, FactSet and Indian fintech (Razorpay, Cred, PhonePe) at every level.