Job Overview
| Particulars | Details |
|---|---|
| Position | Azure Data Engineer |
| Company | Tredence |
| Location | Chennai | Kolkata | Bangalore | Pune |
| Job Type | Full-Time |
| Experience | 1 - 2 years |
| Category / Department | Data Scientist |
| Application Mode |
🏢 About Tredence
Company Overview
Tredence is a global data science and AI solutions company that helps organizations transform data into business value. By combining analytics, artificial intelligence, cloud technologies, and deep industry expertise, Tredence enables enterprises to make smarter decisions and accelerate digital transformation.
Mission
To help organizations unlock measurable business value through advanced analytics, AI, and data-driven decision-making.
Vision
To become the world's most trusted and indispensable analytics partner for global enterprises.
Core Values
• Innovation
• Customer Success
• Collaboration
• Accountability
• Continuous Learning
What Makes Tredence Different?
• Expertise in enterprise AI and advanced analytics.
• Strong focus on business impact through data.
• Industry-specific solutions powered by cloud technologies.
• Collaborative culture with excellent growth opportunities.
Tredence – Bengaluru Office
11th & 12th Floor, Building 2, Prestige Tech Park IV, Amane Bellandur Khane Village, Varthur Hobli, Kadubeesanahalli, Bengaluru – 560103
💡 Editor's Note / Preparation Tip
📝 Resume Tips
• Highlight Azure Data Engineering projects and cloud experience.
• Showcase Azure Databricks and Azure Data Factory implementations.
• Mention PySpark, SQL, and ETL development expertise.
• Include measurable project achievements and optimizations.
• Add relevant Azure or cloud certifications.
🎤 Interview Preparation
• Revise Azure Data Factory architecture and pipeline concepts.
• Practice PySpark transformations and optimization techniques.
• Strengthen SQL query writing and performance tuning skills.
• Review Azure Databricks architecture and workflows.
• Prepare to discuss real-world Data Engineering projects.
💡 Professional Tips
• Demonstrate scalable data pipeline design experience.
• Explain how you've optimized data processing performance.
• Showcase cloud deployment and monitoring knowledge.
• Highlight collaboration with analytics and business teams.
• Stay updated with Azure's latest Data Engineering services.
📝 Job Description
🚀 Hiring | Azure Data Engineer | Tredence
Looking to accelerate your career in Data Engineering and Cloud Analytics? Tredence is hiring Azure Data Engineers who are passionate about building scalable data platforms and solving complex business challenges. If you have experience with Azure technologies, PySpark, and SQL, this is your chance to work on enterprise-grade analytics projects with a global leader in data science and AI.
📌 Position Details
Position: Azure Data Engineer
Company: Tredence
Locations: Chennai | Kolkata | Bangalore | Pune
Work Mode: Hybrid/As Per Business Requirement
Experience: 1–2 Years
Employment Type: Full-Time
Notice Period: Immediate to 30 Days Preferred
⭐ Preferred Skills
✔ Azure Cloud Services
✔ ETL/ELT Development
✔ Big Data Processing
✔ Data Warehousing Concepts
✔ Performance Optimization
🎯 Candidate Requirements
• 1–2 years of experience in Azure Data Engineering.
• Hands-on expertise with Azure Databricks, Azure Data Factory, PySpark, and SQL.
• Strong understanding of data engineering principles.
• Good analytical and troubleshooting skills.
• Excellent collaboration and communication abilities.
• Candidates available within 30 days will be preferred.
🌟 Why Join Tredence?
✅ Work on enterprise-scale Data Engineering and AI projects.
✅ Gain exposure to modern Azure cloud technologies.
✅ Collaborate with highly experienced analytics professionals.
✅ Continuous learning and career development opportunities.
✅ Be part of an innovation-driven and collaborative culture.
✅ Contribute to data solutions that create measurable business impact.
📩 How to Apply
Interested candidates can share their updated resume at:
Know someone who would be a great fit? Tag them or share this opportunity with your network.
🎯 Key Responsibilities
- ✓ Build and maintain scalable Azure-based data pipelines.
- ✓ Develop ETL/ELT workflows using Azure Data Factory.
- ✓ Process and transform large datasets using PySpark.
- ✓ Write optimized SQL queries for data extraction and reporting.
- ✓ Collaborate with analytics and business teams to deliver data solutions.
- ✓ Ensure data quality, reliability, and performance across pipelines.
- ✓ Troubleshoot and optimize cloud-based data workflows.
- ✓ Contribute to enterprise analytics and AI initiatives.
💡 Required Qualifications & Skills
🚀 Career Guidance & Interview Insights
To help you succeed, we've compiled original preparation guides, resume keywords, and growth analytics for this category of role.
Joining as a Azure Data Engineer offers a fantastic opportunity to work at the forefront of technological innovation. You will be exposed to modern software development lifecycles, collaborate with cross-functional product teams, and design scalable architectures that directly impact end-users. The continuous learning curve in tech ensures that your programming, debugging, and system engineering skills remain highly marketable and sharp.
The career roadmap in technology is highly rewarding. Typical progression starts as a Junior Software Engineer, moving to Associate Developer and then Senior Software Engineer (3-6 years). From there, professionals choose between an individual contributor track—becoming a Tech Lead, Staff Engineer, and Principal Architect—or a management track, advancing to Engineering Manager, Director of Engineering, and Chief Technology Officer (CTO).
Expected Technical & Behavioral Questions:
- Q1: How do you optimize database query performance?
Answer Tip: Talk about indexing strategies, query execution plan analysis, avoiding N+1 queries, and implementing caching layers (like Redis). - Q2: Explain the differences between Microservices and Monolithic architecture.
Answer Tip: Highlight scaling advantages, loose coupling, independent deployments, network latency considerations, and data consistency challenges in microservices. - Q3: How do you handle merge conflicts in Git?
Answer Tip: Explain checking out the local branch, pulling the latest main branch, running git merge, opening the conflicted files to resolve blocks manually, and committing the resolved merge.
To pass automated ATS (Applicant Tracking System) screening and catch the recruiter's eye, tailor your resume with the following tips:
- Keywords to include: Software Engineering, SDLC, OOP, CI/CD Pipelines, SQL databases, Agile, Unit Testing, Code Review, Cloud Architectures (AWS/Azure).
- Format: Use a clean, single-column resume format. Avoid graphics, text boxes, or tables which can scramble ATS parser outputs.
- Quantify Results: Instead of writing 'wrote code', write 'Developed a caching system that reduced server response times by 35%.'
Estimated compensation for this role type in India is ₹3,50,000 - ₹6,00,000 per annum (Freshers/Entry level). The actual salary package offered depends on factors such as company size, work mode (remote or on-site), individual technical proficiency, and negotiations during final HR rounds.
Highly recommended certifications include: AWS Certified Solutions Architect, Microsoft Certified: Azure Fundamentals, Certified Kubernetes Administrator (CKA), Oracle Certified Professional Java SE, or tech-stack specific achievements (e.g. Meta Front-End Developer certification).
Frequently Asked Questions
Q. Which locations are available for this role?
Chennai, Kolkata, Bangalore, and Pune.
Q. What experience is required?
1–2 years in Azure Data Engineering.
Q. Which technologies are mandatory?
Azure Databricks, Azure Data Factory, PySpark, and SQL.
Q. What is the preferred notice period?
Immediate to 30 days.
Q. Is cloud experience required?
Yes, hands-on experience with Azure cloud technologies is essential.
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