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Data Analyst

Deel

  • Mumbai, India
  • 3-5 LPA
  • 1 Year
  • Posted Today
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About the role

Zema Global Data Corporation, founded in 1995, has built a reputation as a trusted partner for organisations operating in energy, commodity and financial markets. Over the last two years the company has accelerated its growth through strategic investments and acquisitions, expanding its global footprint and strengthening its data‑driven decision‑making platform. Zema’s mission is to simplify complexity, reduce risk and enable faster, more confident decisions for its customers.

The firm’s culture is anchored on three pillars – Think Big, Make It Happen and Win as One – fostering collaboration, creativity and a purpose‑driven mindset.

The Data Analyst role sits within the Data Operations department and is a critical link between data collection, processing and delivery to Zema’s global client base. Reporting to the Manager, the analyst will work closely with fellow analysts, data developers, product managers and client support specialists to ensure that the C&E (Commodities & Energy) data warehouse receives clean, accurate and timely data. The position is primarily remote but requires quarterly visits to the Navi Mumbai office and flexibility to work rotational shifts covering AU, UK and US time zones.

Key Responsibilities

  • Monitor automated data collection pipelines using proprietary tools, Unix scripting and SQL.
  • Analyse logs, identify root‑causes of collection failures and implement corrective actions.
  • Perform data quality checks, validation and reconciliation to guarantee completeness and timeliness.
  • Respond to client‑raised data discrepancies and coordinate with the Data Development team for code fixes.
  • Communicate with external data vendors via email to resolve file‑format or content issues.
  • Escalate complex processing problems and assist in QA of any pipeline changes.
  • Update and maintain data‑feed documentation and QA checklists.
  • Track all data issues in internal ticketing systems and ensure timely closure.
  • Understand client use‑cases to provide better data‑service recommendations.
  • Contribute to continuous improvement of data‑feed processes and documentation.

Tech Stack & Skills: The role leverages SQL (Oracle/MySQL), Unix/Linux environments, Excel, and basic scripting (Python/Java). Familiarity with ETL concepts, Power BI, and JIRA is a plus. Strong analytical, problem‑solving and communication abilities are essential.

Growth Path: Starting as a junior analyst, high performers can progress to Senior Data Analyst, Data Development Lead, or Product Analytics Manager within 2‑3 years, gaining exposure to global markets and advanced analytics projects.

Why Join Zema Global? You will be part of a fast‑growing, globally recognised data firm that values innovation and offers exposure to real‑world commodity and financial data. The rotational shift model provides a unique opportunity to work with teams across continents, enhancing your cross‑cultural collaboration skills.

Moreover, the blend of remote work and quarterly office interactions offers flexibility while maintaining a strong team bond.

Eligibility & process

Who can apply

Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics or Statistics; minimum 60% aggregate (or CGPA 6.0/10); fresh graduates and candidates with up to 1 year of experience; no active backlogs at the time of joining; strong analytical and communication skills.

Skills & stack

SQL Unix Linux Scripting Data Analysis Advanced Excel Etl Concepts Power BI JIRA

Selection process

  1. Round 1: Online aptitude & logical reasoning test
  2. Round 2: Technical interview covering SQL, Unix scripting and data quality concepts
  3. Round 3: HR interview focusing on cultural fit and career aspirations

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 (SQL, Unix, Linux Scripting, Data Analysis, Advanced Excel, Etl Concepts, Power BI, JIRA) & 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 Deel 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 Deel as a Data Analyst?
Highlight Deel's market reputation, recent tech innovations, and how your skills in SQL 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.
Deel 3-5 LPA
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