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REQUIREMENT_ID_1439 • 3-DAY_ACTIVE_POLICY N

Data Engineer - AWS & Azure

Company
Company HCLTech
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary Competitive Package (Best in Industry)
Location
Location Bengaluru, India
Posted Date
Posted Date Oct 21, 2026
Apply on Official Website ↗
Devops Power Bi Bricks SQL AWS Cd Data Bricks Cd
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Aptitude Practice Questions & Mock Tests Open Resource ↗
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
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Company-Specific Interview Preparation Corner Open Resource ↗
Detailed interview experiences, exam formats, and previous test questions for HCLTech and tech roles.
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Technical Placement Cheat Sheets & Question Bank Open Resource ↗
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
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Algorithm, DSA & Live Code Debugger Practice Open Resource ↗
Hands-on problem sets to improve coding speed and step-by-step memory debugging.

Experience: 8-12 Yrs. Open to matching qualifications.

1
Online Assessment / Technical Interview Rounds / HR Review
Job Title: Data Engineer - Azure & AWS Location: PAN India Experience: 9+ Years Work Mode: Hybrid We are seeking a skilled and motivated Data Engineer to join our team. The ideal candidate will have a strong background in data engineering, data architecture, and data integration. This role involves building and maintaining scalable data pipelines, ensuring data quality and integrity, and supporting data analytics initiatives. You will work closely with internal customers, product owners, core team members, and other stakeholders to ensure that quality data is available, reliable, and easily accessible in a cost effective efficient, scalable way. Key Responsibilities: Data Pipeline Development: Design, build, and maintain robust, scalable, and efficient data pipelines to collect, process, and store large volumes of data from various sources. Data Integration: Integrate data from multiple sources, including APIs, databases, and external datasets, ensuring data consistency and reliability. Data Modelling: Develop and maintain data models and schemas that support efficient data storage, retrieval, and analytics. Database Management: Manage and optimize databases, ensuring their performance, availability, and security Data Quality: Implement and monitor data quality checks to ensure the accuracy, completeness, and consistency of data. Perform analysis required to troubleshoot data related issues and assist in the resolution of data issues. Automation: configure data extraction and load jobs and automate repetitive tasks and processes to improve efficiency and reduce errors. Improve performances of jobs and pipelines by applying optimisation and automation techniques. Documentation: Maintain clear and comprehensive documentation of data pipelines, data models, and data integration processes. Maintenance of time allocation reports. Develop understanding of business/ processes and high-level understanding of high-quality digital product delivery Ways of working: Follow Agile and SDLC processes including the creation of data related user stories. Perform code peer reviews and testing as per SDLC or industry standards. Collaboration: Work closely with internal customers, product owners, various core team members, and other stakeholders to understand their data needs and provide appropriate solutions. Technical collaboration and oversight with Vendors as required. Create SOWs and work packets with vendors as required. Education: Bachelors or Masters degree in computer science, data science, software engineering, information systems or a similar field or equivalent experience. Experience and skills: Over 9 years experience as a Data Engineer or in a similar role. Experience with both Azure & AWS. Experience with data pipeline, ETL and workflow management tools (e.g., Databricks, Data Factory). Proficiency in programming languages such as SQL, Python, R, or Scala. Strong experience with SQL and database management (e.g., MySQL, PostgreSQL, SQL Server). Excellent problem-solving and analytical skills. Strong understanding of data architecture, data modelling, and ETL processes. Ability to work in a fast-paced, dynamic environment and manage multiple tasks simultaneously. Strong communication and collaboration skills. Experience with best practice UX / UI design & development of Business Intelligence data visualisation / exploration tools (Power Bi, Qlik etc) Familiarity with SDLC and Agile ways of working. Familiarity with DevOps tools and practices (e.g. Jenkins, Azure DevOps, etc). Familiarity with Atlassian tools like Bitbucket, JIRA, Confluence. Preferred: GxP and Non GxP SDLC experience Knowledge of data governance and data security best practices. MS Power Platform / power apps experience Cloud DevOps knowledge (e.g. Terraform) Certifications in cloud data technologies (e.g. Azure Data Fundamentals) Basic data science experience and knowledge. Other: English language required. May require travel 10-20% of time based on project locations.

HCLTech — Data Analytics & SQL Interview Guide

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

APTITUDE & LOGIC 📖
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 ↗
COMPANY GUIDE 🎯
HCLTech Interview Preparation Corner

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

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

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

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

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

Open Resource ↗
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 (Devops, Power Bi, Bricks, SQL, AWS, Cd, Data Bricks, Cd) & 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
HCLTech Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
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.
Why do you want to join HCLTech as a Data Engineer - AWS & Azure?
Preparation Tip: Highlight HCLTech's market reputation, recent tech innovations, and how your skills in Devops 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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