Bangalore’s IT hiring market has two names that show up constantly in fresher job searches: NTT DATA and IBM. Both regularly hire for entry-to-mid-level tech roles in the 5–10 LPA range, and both attract the same pool of candidates — B.Tech/B.E. graduates and early-career professionals with 0–3 years of experience. Here’s what’s actually worth knowing about how these companies typically hire, even outside any one specific listing.

Why these two companies keep showing up together

NTT DATA and IBM aren’t competitors in the way two startups might be — they’re both large, India-heavy IT services and consulting operations that hire in volume, especially out of Bangalore and Hyderabad. NTT DATA runs global delivery centers supporting clients across banking, healthcare, and manufacturing. IBM’s India operations span everything from cloud consulting to hardware R&D. For a fresher, the practical difference is less about brand prestige and more about which specific team and technology stack you land in — that varies far more within each company than between them.

Quick comparison

What the NTT DATA roles actually involve

Most fresher-level NTT DATA openings in this salary band are Business Analyst or Data Analyst positions supporting a specific client account. Day to day, that usually means pulling and cleaning data in SQL or Excel, building reports (often in Power BI), and communicating findings to a client-facing team lead. It’s less “build a product from scratch” and more “make sense of a client’s data and present it clearly” — a genuinely useful skill to build early, even if it’s less flashy than pure software development.

What the IBM roles actually involve

IBM’s entry-level tech roles in this bracket tend to be more hands-on-code — associate software engineer positions where you’re writing and testing code (commonly Java or Python), often on cloud infrastructure projects. IBM’s scale means you’re more likely to be one of many engineers on a large, established codebase rather than owning a feature end-to-end from day one, which is normal for a first job at a company this size.

How to prepare for either interview process

• For NTT DATA-style analyst roles: practice writing SQL joins and aggregate queries — this comes up in nearly every analyst screening. Be ready to walk through a dashboard or report you’ve built, even if it was for a college project.
• For IBM-style engineering roles: revise data structures and basic algorithm questions (arrays, strings, sorting). Have a GitHub repo, even a small one, that you can talk through confidently.
• For both: the HR round usually covers notice period, relocation willingness, and shift flexibility — have honest, decided answers ready rather than figuring it out on the spot.

A note on salary expectations

The “5–10 LPA” range you’ll see in listings is wide for a reason — it usually reflects a spread across different sub-roles and experience bands within the same job title, not a negotiable range for every single candidate. A genuine fresher with no prior internship is more realistically looking at the lower half of that range; the upper end tends to go to candidates with a relevant internship, certification (like an AWS or Azure associate cert), or a strong academic project portfolio.

Before you apply

• Check both companies’ official career portals directly for current openings — this comparison reflects an October 2025 snapshot, and specific listings from that period are likely closed.
• Match your resume’s keywords to the specific job description rather than sending one generic resume to both.
• If given a choice between the two, think about which day-to-day work suits you more — analyst-style data/communication work, or engineer-style coding — rather than picking purely by brand name.

Written by Babu Addakula, Job Visit.

NTT DATA previously hired for Business Analyst and Data Analyst roles out of its Bangalore office, in the 5–10 LPA range, open to both freshers and experienced candidates. Here’s what this kind of role genuinely involves, what actually gets you shortlisted, and how to prepare — without the recruitment-brochure language most listings bury this in.

Business Analyst vs. Data Analyst — What’s Actually Different

The two titles get used almost interchangeably in job postings, but the day-to-day work does differ, even at the same company. A Business Analyst is essentially a translator — they sit with stakeholders, figure out what the actual business problem is, and turn that into requirements a technical team can build against. A Data Analyst is more of an investigator — they go into the data itself, clean it, query it, and come back with evidence that answers a specific question.

At a company the size of NTT DATA, you’ll likely specialize in one, though the boundary blurs often — a BA who can write a decent SQL query is far more useful than one who can’t, and a DA who understands business context produces far more relevant analysis than one who only knows the data.

What a Realistic Day Looks Like

Mornings usually start with an Agile team stand-up, followed by writing or refining user stories in JIRA. Mid-morning tends to involve actual SQL work — pulling something specific like customer churn or sales data from a warehouse. Afternoons often mix a stakeholder meeting to align on a sprint’s goals with heads-down time building a dashboard in Power BI or Tableau, sometimes followed by presenting findings to a small panel of stakeholders. It’s a genuine mix of technical focus time and real conversation, not one or the other.

Skills That Actually Matter in the Interview

SQL is non-negotiable. You need to comfortably write queries involving joins, aggregations, and filtering — this gets tested directly in technical rounds, often as a live exercise rather than a multiple-choice question.

Data visualization matters almost as much — hands-on experience with Power BI or Tableau, specifically being able to build a dashboard that tells a clear story rather than just displaying numbers, is what separates candidates who can talk about tools from candidates who can actually use them.

Excel is still relevant, even at a company this size — pivot tables, XLOOKUP, and basic data modeling come up more often than people expect, especially for quick ad-hoc requests that don’t justify spinning up a full SQL query.

Basic statistics — mean, median, standard deviation, correlation vs. causation — matter more for the Data Analyst track specifically, since it’s what separates genuinely useful analysis from a chart that looks convincing but says nothing reliable.

On the soft-skills side, stakeholder management and clear communication carry real weight — you’ll regularly explain a technical finding to someone non-technical, and how well you do that is often judged as closely as your technical answers.

Building a Portfolio Without Corporate Experience

If you’re a fresher, the single most convincing thing you can bring to an interview is a capstone project: pick a public dataset (Kaggle and most government open-data portals are good sources), define a real business question, clean and analyze the data in SQL or Python, and build a dashboard in Tableau or Power BI presenting your findings. Document the whole process in a GitHub repo or a short write-up — a hiring manager learns more from seeing your actual work than from any list of tools on your resume.

If you’re coming in with prior experience, pick your two or three strongest projects and prepare to walk through them using the STAR method (Situation, Task, Action, Result) — with a clear emphasis on the actual business impact your analysis had, not just the technical steps you took.

What the Interview Process Tends to Look Like

Expect three stages: a short HR screening call covering background and compensation expectations, a technical round that includes live SQL work and a business case study (something like “why did user logins drop last quarter?” walked through out loud), and a final managerial/culture-fit conversation with behavioral questions about handling disagreements with stakeholders or past project challenges.

The case-study round is where most candidates either stand out or blend in — interviewers are watching how you structure your thinking out loud, not whether you land on a “correct” answer immediately.

Before you apply to similar roles

• Check NTT DATA’s own careers page directly for current openings — this specific listing is from October 2025 and is likely closed.
• Match your resume’s language to the actual job description — mention SQL, stakeholder management, and the specific visualization tool you know.
• Have one real project (even a self-built one) you can explain confidently for five minutes, including what you’d do differently now.

Written by Babu Addakula, Job Visit.

Infor previously hired for Software Engineer, Associate roles in Hyderabad, aimed at recent graduates rather than experienced hires. If you’re finishing a B.Tech or M.Tech in computer science (or something close to it), this breakdown is a useful reference for what this kind of structured, mentored entry point at an enterprise software company actually looks like — even if this specific listing has closed.

What Infor actually does

Infor builds business software for specific industries rather than one-size-fits-all tools — separate product lines for manufacturing, healthcare, and retail, for example, instead of a single generic ERP. The company is owned by Koch Industries, which means it isn’t chasing quarterly stock targets the way a publicly listed company would. In practical terms, that tends to mean steadier product timelines and less of the reactive churn you sometimes see at newer startups.

As a fresher, you won’t be working on flashy consumer apps here — you’ll likely touch enterprise modules like ERP, supply chain, or HR software used by large manufacturing or retail companies. It’s less glamorous than building the next social app, but the problems are real and the codebases are mature, which is a different (and useful) kind of learning experience than a scrappy startup.

What the role involves

You’d join an Agile team, which in practice means daily standups, sprint planning every couple of weeks, and code reviews where senior engineers actually read what you wrote and tell you what to fix. That last part matters more than it sounds — code review is where a lot of real learning happens in your first year, more than any onboarding document will teach you.

Expect a mix of Java, and depending on the team, Python or JavaScript. SQL comes up constantly since enterprise software lives and dies by its databases. If you’ve used Git for anything beyond a college project — even just pushing to a personal GitHub repo — that experience will help more than most people expect.

Salary and location

This listing was in the 5–7 LPA range for the Hyderabad office. That’s a reasonable, not exceptional, fresher package for a large IT company in Hyderabad — roughly in line with what similar-sized enterprise software firms pay entry-level engineers in the city. Don’t expect a startup-style equity story; this is a steady, benefits-heavy package (health insurance, PTO, and typically some learning/certification reimbursement).

What the interview process tends to look like

For roles like this, the typical pipeline runs: an online assessment (aptitude + a couple of coding problems, usually on HackerRank-style platforms), followed by one or two technical interviews focused on data structures and your own projects, and finally an HR conversation about compensation and joining timelines.

The one piece of advice that consistently helps freshers in these interviews: be ready to explain your own project in detail — not just what it does, but why you made the choices you made. Interviewers often care more about how you think through a problem than whether you get the “optimal” answer immediately.

Before you apply to similar roles

• Check Infor’s own careers page directly for current openings — this specific listing is from September 2025 and is likely closed.
• Tailor your resume to mention SQL and at least one backend language explicitly — enterprise software teams screen for this directly.
• Have one project you can talk about for five minutes straight, including a mistake you made and fixed.

Written by Babu Addakula, Job Visit.