Data Analyst — Fresher / Trainee (Hyderabad, 2026)

About the role

Entry-level data analyst role at InfoHive in Hitec City — Excel, SQL, Power BI and basic Python on real client datasets across retail, BFSI and SaaS. Strong fit for graduates with logical aptitude who want to break into analytics without prior industry experience.

Hyderabad's analytics market in 2026 is genuinely hot. Every tier-2 SaaS firm, every Hitec City fintech, every retail and pharma captive is hiring junior analysts faster than the supply of credible freshers can keep up — which is exactly why mid-size services firms like InfoHive Solutions can take a chance on graduates with no prior industry experience and train them up in three to four months. The current 2026 listing is for a Data Analyst Trainee, transitioning to confirmed Data Analyst after a 90-day probation, with a starting CTC band of INR 3 to 6 lakh depending on degree, prior project work and the candidate's depth on SQL and Excel.

The core job is what every junior analyst job in India is: take messy client data, make it clean, make it correct, and turn it into something a non-technical stakeholder can act on by Monday morning. In a typical week you might be handed a client's three-year sales export with inconsistent product codes, asked to reconcile it against the marketing spend file from a separate team, build a Power BI dashboard that shows return on ad spend by region and channel, and walk the client's marketing manager through it on a Wednesday call. The work is roughly 40 percent data cleaning, 30 percent SQL and Excel modelling, 20 percent dashboard building in Power BI or Tableau, and 10 percent storytelling — which means writing the two-paragraph summary at the top of the dashboard that tells the stakeholder what to actually do.

The technical bar at the entry stage is realistic. You need to be genuinely fluent in Excel — pivot tables, VLOOKUP and XLOOKUP, INDEX-MATCH, basic data cleaning with Power Query, conditional formatting that does not crash the file. You need working SQL — joins (inner, left, full), GROUP BY with HAVING, window functions at least at the ROW_NUMBER and RANK level, and the discipline to write a query that someone else can read six months later. Power BI or Tableau at a beginner level — being able to load a CSV, build a clean visual, set up a basic measure in DAX or a calculated field — is enough to start, with the depth picked up on the job. Python is welcome but not required at this stage; the senior analysts on your team will pull you into pandas and basic forecasting in your second year.

What the role does not require, and what most freshers worry about unnecessarily, is a statistics or computer-science background. InfoHive hires from any quantitative discipline — B.Com, BBA, B.Sc Statistics, B.Sc Computer Science, B.Tech, MBA freshers. What it screens for instead is logical thinking under pressure. The technical interview round is essentially a case study: here is a CSV, here are three business questions, sit at a laptop for 45 minutes and tell us what you find. Candidates who structure the work calmly — start with shape and quality, then pivot to the question, then sanity-check before drawing conclusions — clear the loop at a much higher rate than candidates who jump straight to a chart.

Training at InfoHive runs as a structured 12-week onboarding programme. Weeks one to two are SQL and Excel intensives — daily homework, daily review. Weeks three to four are Power BI fundamentals built around a real anonymised retail dataset. Weeks five to six are introduction to Python and pandas. Weeks seven to nine are paired work with a senior analyst on a live but low-stakes client deliverable. Weeks ten to twelve are a capstone project that you present to a panel of senior analysts and your manager. Trainees who clear the capstone successfully are confirmed as Data Analyst on the spot with a CTC step up of roughly 15 to 25 percent.

Career growth out of this role is one of the cleanest paths in Indian tech. Twelve to eighteen months in, you are a confirmed Data Analyst running your own dashboards. Two to three years in, you are a Senior Analyst owning a client relationship, managing one or two juniors, and presenting in client steering committees. Three to five years in, the fork appears: an Analytics Manager track inside a services firm, a Senior Analyst or Data Scientist track at a product company (Razorpay, PhonePe, Swiggy, Cred, Zerodha all hire at this level from services backgrounds), or an MBA exit if you decide the path forward is product or strategy rather than deeper technical work. The market premium for two years of clean analytics experience is genuine — typical jumps at the two-year mark are 70 to 120 percent on base, especially for analysts who have learned SQL beyond surface level and have built one credible portfolio dashboard.

For freshers preparing to apply, the single highest-leverage thing you can do this month is build a portfolio. Pick any dataset from Kaggle (a Spotify listening dataset, a Bangalore real-estate dataset, a Zomato restaurants dataset all work), do the full cleaning and analysis in SQL and Power BI, write the result up on a free Notion page, and link it from your CV and LinkedIn. Recruiters scan portfolios in 60 seconds; a well-told end-to-end project will move your CV ahead of three years of unrelated coursework.

Responsibilities

Clean and validate client datasets in Excel and SQL. Build and maintain Power BI / Tableau dashboards. Run ad-hoc SQL queries to answer business questions. Document data definitions and dashboard logic. Present findings to internal and client stakeholders. Pair with senior analysts on capstone projects during onboarding.

Requirements & qualifications

Bachelor's degree in any quantitative discipline — B.Com, BBA, B.Sc, B.Tech, MBA fresher. Strong Excel (pivots, lookups, Power Query). Working SQL (joins, GROUP BY, window functions). Familiarity with Power BI or Tableau. Logical thinking and curiosity about data. Strong written English for client deliverables.

Why this role in 2026

Real entry into Hyderabad's analytics market with a structured 12-week onboarding programme. Direct exposure to client data and stakeholders from month one, with a clean two-year path to Senior Analyst or a product-company exit at a 70-120% comp jump.

Application tips

Build a one-page portfolio (Notion or GitHub) with one end-to-end project — Kaggle dataset, SQL cleaning, Power BI dashboard, written summary. Link it from your CV and LinkedIn. Apply via the Naukri listing or InfoHive's careers page; reference your portfolio in the cover note.

Interview preparation

Three rounds: aptitude (numerical and logical), a 45-minute case-study round on a real CSV, and a behavioural and HR round. For the case study, practise on Kaggle datasets and time yourself — the trick is structured exploration, not speed. Brush up on SQL joins, window functions and basic pandas before the round.

Career growth

Data Analyst Trainee → Data Analyst (after 12-week capstone) → Senior Data Analyst (year 2) → Analytics Manager / Data Scientist / external product-company exit (year 3-5).

Company & benefits

Health insurance for self and family, paid Power BI / Tableau / SQL certifications, hybrid working (3 days office), gratuity, performance bonus, and access to a curated internal learning library for SQL, Python and ML self-study.