Data Analyst / Developer (SQL, Power BI, ...)

The L&T interview process typically starts with a timed online aptitude test followed by a technical interview focusing on SQL query writing, Power BI scenario questions and basic Python/ML concepts. The final HR round assesses cultural fit, communication skills and salary expectations. Candidates should practice data‑manipulation problems and be ready to discuss any academic projects related to analytics.

L&T Energy Hydrocarbon promotes a performance‑driven yet supportive work culture where learning is encouraged through regular trainings and mentorship. Employees enjoy a balanced work‑life schedule, clear career ladders, and opportunities to work on high‑impact energy projects across India and abroad.

Bachelor’s degree in Computer Science, Data Science, Information Technology, Engineering (any branch) or Statistics with a minimum of 60% aggregate (or CGPA 6.5/10). Final year students of the 2026 batch are eligible. No active backlogs are allowed at the time of joining. Candidates should have basic knowledge of SQL, Power BI and Python.

Round 1: Online Aptitude Test (quantitative, logical reasoning, English) → Round 2: Technical Interview (SQL, Power BI, Python, basic ML concepts) → Round 3: HR Interview (fitment, motivation, salary discussion)

Larsen & Toubro (L&T) Energy Hydrocarbon division is a cornerstone of India’s energy infrastructure, delivering end‑to‑end solutions for offshore and onshore hydrocarbon projects. The Offshore Hazira Manufacturing Complex, situated in Gujarat, is a high‑tech hub that manufactures critical equipment for offshore drilling, processing, and power generation. With a legacy of over six decades, L&T Energy Hydrocarbon blends engineering excellence with cutting‑edge digital initiatives, fostering an environment where technology drives operational efficiency and sustainability. As part of its digital transformation journey, L&T is building a robust data analytics capability to turn massive operational data streams into actionable insights. The Data Analyst / Developer role is designed for fresh graduates who are eager to apply their academic knowledge in SQL, Power BI, and Python to real‑world energy projects. You will work closely with senior data scientists, business analysts, and engineering teams to create data pipelines, dashboards, and simple machine‑learning models that support decision‑making across the complex. **Key Responsibilities** 1. Write, optimise and maintain SQL queries for data extraction from SQL Server, MySQL or PostgreSQL databases. 2. Perform data cleaning, transformation, and validation to ensure high‑quality datasets. 3. Assist in designing and implementing ETL pipelines for automated data flow. 4. Develop interactive Power BI dashboards, data models, DAX calculations and KPI visualisations. 5. Translate business requirements into clear, insightful visual reports for stakeholders. 6. Conduct exploratory data analysis (EDA) using Python libraries such as Pandas and NumPy. 7. Build and evaluate basic machine‑learning models (regression, classification) using Scikit‑learn. 8. Document code, data dictionaries and analytical procedures for reproducibility. 9. Collaborate with cross‑functional teams to understand data needs and support ongoing projects. 10. Prepare presentations and technical documentation for senior leadership. **Tech Stack**: SQL (joins, window functions), Power BI (DAX, data modelling), Python (Pandas, NumPy, Scikit‑learn, Matplotlib, Seaborn), Excel, Git for version control. **Growth Path**: Starting as a Data Analyst / Developer, high performers can progress to Senior Analyst, Data Engineer, or Machine‑Learning Engineer roles within L&T’s analytics centre of excellence. The exposure to large‑scale energy data and mentorship from seasoned data scientists accelerates career growth. **Why Join L&T Energy Hydrocarbon?** L&T offers a stable, reputable platform with competitive remuneration, structured learning programmes, and the chance to contribute to nation‑building energy projects. The company’s emphasis on continuous upskilling, mentorship, and a collaborative culture makes it an ideal launchpad for aspiring data professionals.