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JD #2396
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Data Analyst

JLL

  • Gurugram, Haryana
  • 4-6 LPA
  • Fresher (0-1 Yrs)
  • Posted Oct 29, 2026
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About the role

JLL (Jones Lang LaSalle) is a global leader in real‑estate services, operating in more than 80 countries. In India, JLL combines deep market knowledge with cutting‑edge technology to help clients optimise their real‑estate portfolios, create sustainable workplaces and drive value. The company’s culture is built around collaboration, innovation and a strong commitment to professional growth, making it an attractive destination for fresh talent looking to launch a career in corporate real‑estate and data analytics. The Workplace Data Administrator (Data Analyst) role sits within the Workplace Management / Real Estate Operations function at JLL’s Gurgaon office. Reporting to the Workplace Data Manager, the incumbent will be the custodian of the Integrated Workplace Management System (IWMS) data, ensuring that building, floor, room and workspace information is accurate, up‑to‑date and aligned with the physical environment. The role blends data administration, basic CAD drafting, and business‑intelligence reporting to support facilities, corporate real‑estate and project teams. **Key Responsibilities** 1. Maintain and update workplace and space records in the IWMS, following global data standards and naming conventions. 2. Perform data cleansing, validation and periodic quality audits to eliminate duplicates and inconsistencies. 3. Collect, organise and analyse large datasets to identify utilisation trends, capacity gaps and cost‑saving opportunities. 4. Design and deliver dashboards and visual reports using Powerβ€―BI and Excel for senior stakeholders. 5. Manage floor‑plan information, reconcile CAD drawings with IWMS records, and support updates after moves or refurbishments. 6. Provide basic AutoCAD support – updating room boundaries, space layouts and preparing files for upload. 7. Produce regular and ad‑hoc reports on space allocation, occupancy, desk utilisation and other workplace assets. 8. Collaborate with Facilities, Projects, Moves and Corporate Real‑Estate teams to gather accurate data and resolve discrepancies. 9. Contribute to the implementation of data‑governance policies and continuous‑improvement initiatives. 10. Document changes, maintain audit trails and ensure compliance with internal controls. **Tech Stack**: Microsoft Excel, Powerβ€―BI, AutoCAD (basic), Integrated Workplace Management System (e.g., IBMβ€―TRIRIGA, Planon, Archibus), SQL/Access for data extraction, and standard office productivity tools. **Growth Path**: Starting as a Workplace Data Administrator, high‑performers can progress to Workplace Data Analyst, IWMS Administrator, Space Management Analyst, or even senior roles such as Space Management Lead. JLL’s internal mobility program and structured learning platforms provide clear pathways for skill‑upgradation and leadership development. **Why Join JLL?** JLL offers exposure to world‑class real‑estate projects, a collaborative multicultural environment, and a strong emphasis on technology‑driven workplace solutions. Fresh graduates gain hands‑on experience with enterprise‑grade IWMS platforms, develop analytical and CAD skills, and receive mentorship from industry experts, positioning them for a rewarding career in real‑estate analytics and facilities management.

Eligibility & process

Who can apply

Graduates (B.Tech/B.E., B.Sc., B.Com, BBA or equivalent) from any stream with a minimum of 60% aggregate. Freshers from the 2024‑2025 batch are preferred. No active backlogs at the time of joining. Candidates should have basic knowledge of Excel, Powerβ€―BI and an interest in CAD or data management.

Skills & stack

Data Administration Microsoft Excel Power BI Autocad Iwms Familiarity SQL Access Stakeholder Management

Selection process

  1. Round 1: Online aptitude & logical reasoning test
  2. Round 2: Technical interview (data handling, Excel/Powerβ€―BI, basic CAD)
  3. Round 3: HR interview (fitment, communication, career goals)

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Data Administration, Microsoft Excel, Power BI, Autocad, Iwms Familiarity, SQL, Access, Stakeholder Management) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion JLL Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join JLL as a Data Analyst?
Highlight JLL's market reputation, recent tech innovations, and how your skills in Data Administration directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
JLL 4-6 LPA
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