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Data Analyst

Golden Management Services

  • Bengaluru, India
  • β‚Ή3.25 LPA – β‚Ή7.5 LPA
  • Internship
  • Posted Today
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About the role

Golden Management Services is a mid‑size IT services and consulting firm that has been operating in India for over a decade. The company focuses on delivering data‑driven solutions to clients across banking, retail, and manufacturing sectors. With a strong emphasis on continuous learning, Golden Management Services invests in up‑skilling its workforce through internal workshops, certifications, and mentorship programs.

The organization prides itself on a collaborative culture where junior talent works side‑by‑side with seasoned data scientists, enabling rapid knowledge transfer and real‑world exposure.

As a Data Analyst at Golden Management Services, you will be the backbone of the analytics team, turning raw data into actionable insights for business stakeholders. The role is designed for fresh graduates and early‑career professionals who have a solid foundation in Excel, SQL, and basic programming concepts. You will get hands‑on experience building dashboards, preparing MIS reports, and ensuring data quality across multiple projects.

The hybrid work model allows you to work from the office for collaborative sessions while also providing flexibility to work remotely for focused analysis tasks.

Key Responsibilities

  • Collect, clean, and transform data from various sources to support analytical projects.
  • Perform exploratory data analysis to uncover trends, patterns, and anomalies.
  • Develop and maintain MIS and ad‑hoc reports using Microsoft Excel and Power BI.
  • Write efficient SQL queries to extract and manipulate data from relational databases.
  • Create basic visualizations and interactive dashboards for business users.
  • Validate data accuracy and resolve inconsistencies in collaboration with data engineers.
  • Document data pipelines, reporting logic, and standard operating procedures.
  • Support senior analysts in preparing presentation‑ready insights for decision‑makers.
  • Participate in cross‑functional meetings to understand business requirements and translate them into analytical solutions.
  • Continuously improve data quality processes and suggest automation opportunities.

Tech Stack: Microsoft Excel, SQL, Power BI, Python (basic), data cleaning tools, and version‑controlled notebooks.

Growth Path: Starting as a Data Analyst, high performers can progress to Senior Analyst, then to Data Scientist or Analytics Manager within 2‑4 years, depending on skill acquisition and project impact. The company encourages certifications in Tableau, AWS, and advanced analytics, which are supported financially.

Why Join: Golden Management Services offers a vibrant learning environment, exposure to real‑world client projects, and a clear career trajectory. The hybrid model ensures a balanced work‑life experience, while the supportive culture fosters mentorship and peer learning. If you are eager to build a solid foundation in data analytics and grow with a forward‑thinking firm, this role is an excellent launchpad.

Eligibility & process

Who can apply

Bachelor's degree in any discipline (Engineering, Science, Commerce, Arts) with minimum 60% aggregate; recent graduates or final‑year students (2024‑2025 batch) eligible; no active backlogs at the time of joining; basic knowledge of Microsoft Excel and data analysis concepts; familiarity with SQL, Power BI, or Python is a plus; strong analytical, logical‑thinking, and communication skills.

Skills & stack

Microsoft Excel Data Analysis SQL Power BI Python Data Cleaning Data Validation Mis Reporting

Selection process

  1. Round 1: Online Aptitude Test (logical reasoning, quantitative, verbal)
  2. Round 2: Technical Interview (Excel functions, SQL queries, basic Python/PBI concepts)
  3. Round 3: HR Interview (fitment, communication, 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 (Microsoft Excel, Data Analysis, SQL, Power BI, Python, Data Cleaning, Data Validation, Mis Reporting) & 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 Golden Management Services 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 Golden Management Services as a Data Analyst?
Highlight Golden Management Services's market reputation, recent tech innovations, and how your skills in Microsoft Excel 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.
Golden Management Services β‚Ή3.25 LPA – β‚Ή7.5 LPA
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