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REQUIREMENT_ID_59 β€’ 3-DAY_ACTIVE_POLICY

Associate – Platform Services / Data Engineer

Company
Company jobs.zs.com
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 7 LPA
Location
Location Pune / Gurgaon
Posted Date
Posted Date Today
ETL SQL Python Data Modeling Data Warehousing AWS Azure Hadoop Spark PySpark Informatica Talend SSIS Agile Version Control Git Data Quality KPI Development Cloud Services
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Data Engineering Fundamentals Open Resource β†—
Provides foundational knowledge of ETL, data modeling, and data warehousing concepts essential for the role.
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Technical Interview Preparation Open Resource β†—
Offers practice on SQL, Python, and data engineering scenarios commonly asked in interviews.
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Project‑Based Learning Open Resource β†—
Helps build real‑world data pipelines and analytics projects to showcase skills to recruiters.
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Algorithmic Problem Solving Open Resource β†—
Improves coding skills and problem‑solving speed for technical interviews.

Bachelor’s or Master’s degree in Computer Science, MIS, Information Technology, or a related discipline. 1–2 years of relevant development experience. Preference for experience in medium‑to‑large technology solution delivery engagements and Pharma or Life Sciences domains. Strong ETL, SQL, Python, data modeling, and data warehousing skills. Fluency in English and a client‑first mindset are required. No specific backlog policy mentioned.

1
Round 1: Technical – SQL, Python, ETL concepts
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Round 2: Technical – Data modeling, cloud, platform configuration
3
Round 3: HR and cultural fit
ZS, a global consulting and technology firm, has a strong presence in India with offices in Pune and Gurgaon. The company specializes in data-driven solutions for clients across industries such as Pharma, Life Sciences, Finance, and Retail. With a focus on analytics, AI, and digital transformation, ZS empowers businesses to make data‑centric decisions and drive measurable outcomes. The firm is known for its collaborative culture, continuous learning environment, and emphasis on client impact. The Associate – Platform Services / Data Engineer role is designed for early‑career professionals who want to work at the intersection of data engineering, analytics, and AI. The primary responsibility is to build scalable, analytics‑ready, and Agentic AI‑ready data products on the ZAIDYN platform. This involves designing, developing, and maintaining end‑to‑end ETL pipelines that ingest data from diverse sources, validate and transform it using SQL and Python, and load it into data warehouses or analytics databases. The engineer will also create data models, define KPIs, and ensure that the resulting data products are reliable, well‑documented, and ready for downstream BI and AI use cases. Key responsibilities include: 1. Designing and implementing ETL pipelines using SQL and Python. 2. Performing data extraction, validation, transformation, and loading across multiple source systems. 3. Building data models (conceptual, logical, physical) and dimensional schemas for analytics. 4. Developing KPI definitions and ensuring consistency across reports. 5. Optimizing query performance and ensuring data quality through validation checks. 6. Configuring and extending solutions on the ZAIDYN platform. 7. Collaborating with data scientists, BI developers, and cloud teams to deliver end‑to‑end data products. 8. Participating in Agile ceremonies, code reviews, and documentation. 9. Supporting client communication and project status reporting. 10. Mentoring junior team members and coordinating cross‑functional work. Tech stack: SQL (T‑SQL, PostgreSQL, Snowflake), Python (pandas, PySpark), data modeling tools, ETL platforms (Informatica, Talend, SSIS), cloud services (AWS, Azure), big‑data technologies (Hadoop, Spark/PySpark), and version control (Git). Growth path: Starting as an Associate, professionals can progress to Senior Data Engineer, Lead Data Engineer, or Platform Architect roles. ZS offers structured learning pathways, mentorship, and opportunities to work on high‑impact projects across multiple industries. Why join ZS? The firm offers competitive compensation, exposure to cutting‑edge analytics and AI platforms, a collaborative global environment, and a clear career ladder. Employees benefit from continuous training, industry certifications, and the chance to work with leading clients in the Pharma and Life Sciences sectors. Overall, this role is ideal for data engineers who are eager to build robust data products, learn new platform technologies, and contribute to client success in a dynamic consulting setting.

jobs.zs.com β€” QA & Automation Testing Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
jobs.zs.com Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for jobs.zs.com and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
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 (ETL, SQL, Python, Data Modeling, Data Warehousing, AWS, Azure, Hadoop, Spark, PySpark, Informatica, Talend, SSIS, Agile, Version Control, Git, Data Quality, KPI Development, Cloud Services) & 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
jobs.zs.com Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between Implicit Wait, Explicit Wait, and Fluent Wait in Selenium? Answer β–Ό
Model Answer: Implicit Wait sets a global timeout for all element lookups. Explicit Wait pauses execution until a specific ExpectedCondition (e.g. elementToBeClickable) is met. Fluent Wait allows defining polling frequency and ignoring specific exceptions like NoSuchElementException.
Explain the Page Object Model (POM) and its advantages in Test Automation. Answer β–Ό
Model Answer: POM is a design pattern that creates an object repository for web UI elements. It separates test scripts from page locators, reducing code duplication and making maintenance easy when UI elements change.
How do you handle dynamic WebElements whose ID changes on page reload? Answer β–Ό
Model Answer: Use dynamic XPath methods like contains(), starts-with(), text(), or XPath axes (ancestor, following-sibling, parent) instead of brittle absolute paths.
What is the difference between @BeforeMethod and @BeforeClass in TestNG? Answer β–Ό
Model Answer: @BeforeClass runs once before the first test method in the current class, while @BeforeMethod executes before each individual test method.
How do you validate REST API response codes and JSON payload using Postman / RestAssured? Answer β–Ό
Model Answer: In RestAssured: given().when().get('/endpoint').then().assertThat().statusCode(200).body('status', equalTo('ACTIVE')).
Why do you want to join jobs.zs.com as a Associate – Platform Services / Data Engineer?
Preparation Tip: Highlight jobs.zs.com's market reputation, recent tech innovations, and how your skills in ETL directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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