Job Overview
| Particulars | Details |
|---|---|
| Position | Principal Data Engineer |
| Company | nHRMS |
| Location | Dehradun, Uttarakhand |
| Job Type | Full-Time |
| Category / Department | IT |
| Application Mode |
🏢 About nHRMS
About nHRMS
nHRMS, short for Nurturing Human Resources & Management Systems, is a strategic HR solutions and consulting organization focused on helping businesses transform their people, processes, and workforce capabilities.
The company provides end-to-end HR solutions covering talent acquisition, executive search, HR advisory, HR technology, leadership development, organizational strategy, learning solutions, and other workforce-related services.
According to the company's website, nHRMS has 16+ years of experience, 423 clients across 14 countries, and 1,000+ leaders placed.
Company Mission:
nHRMS aims to help organizations achieve exceptional performance through their people by providing innovative and customized HR solutions aligned with business objectives.
Company Vision:
The company's vision is to become a trusted HR management consulting partner recognized for expertise, innovation, and measurable impact on organizational success.
Core Values:
Excellence
Innovation
Integrity
Partnership
Key Services
Talent Acquisition
Executive Search
HR Advisory
Fractional HR Solutions
HR Technology
Leadership Development
Organization Strategy
Learning Solutions
Compliance & Operations
nHRMS describes its approach as people-first, data-driven, collaborative, and agile.
nHRMS – Nurturing Human Resources & Management Systems
Office Locations:
United States | Hyderabad, India | Bangalore, India
💡 Editor's Note / Preparation Tip
Resume Tips:
Principal Data Engineer candidates should clearly highlight:
Total data engineering experience
GCP implementation projects
Azure implementation projects
BigQuery
Dataflow
Pub/Sub
Dataproc
Cloud Composer
Azure Data Services
Python
SQL
Spark
Kafka
Data modelling
Data Mesh / Data Fabric
Data governance
Data quality
Data observability
Terraform
CI/CD
GitHub Actions
Cloud Build
Vertex AI
AI/GenAI projects
Architecture leadership
Team mentoring
Pre-sales and PoC experience
Make Your Resume Results-Oriented
Instead of simply listing technologies, demonstrate measurable outcomes.
For example:
Designed a cloud data platform processing millions of records daily.
Reduced pipeline processing time by X%.
Migrated legacy workloads from on-premises infrastructure to GCP/Azure.
Implemented real-time streaming using Kafka and Pub/Sub.
Established data-quality and observability frameworks.
Reduced cloud infrastructure costs by X%.
Led a team of X data engineers.
Designed enterprise-wide data governance standards.
Interview Preparation:
Prepare for senior-level questions around:
GCP
BigQuery architecture
Dataflow
Pub/Sub
Dataproc
Cloud Composer
Cloud Storage
GCP security
GCP cost optimization
Azure
Azure Data Factory
Azure Databricks
Azure Synapse
Azure Data Lake
Azure Event Hubs
Azure storage services
Azure security and governance
Data Architecture
Data Mesh
Data Fabric
Lakehouse architecture
Enterprise data platforms
Data products
Data governance
Data quality
Data observability
Distributed & Streaming Systems
Kafka
Pub/Sub
Event-driven architecture
Stream processing
Exactly-once vs at-least-once processing
Event ordering
Fault tolerance
Leadership
Be prepared to discuss:
Architecture decisions
Technology selection
Cloud migration
Team mentoring
Architecture reviews
Stakeholder management
Pre-sales engagements
Proofs of concept
Technical strategy
📝 Job Description
Position Overview
nHRMS is looking for a highly experienced Principal Data Engineer who can lead the architecture and implementation of enterprise-scale data and analytics platforms across GCP and Azure.
The role combines hands-on technical leadership, cloud data engineering, architecture, data governance, technology strategy, mentoring, and stakeholder engagement.
The successful candidate will be responsible for designing scalable data platforms, defining data models, leading cloud implementations, evaluating technologies, mentoring technical teams, and contributing to pre-sales and proof-of-concept initiatives.
Compensation
Budget: Up to ₹40 LPA
Final compensation may depend on experience, technical expertise, interview performance, and role fit.
Candidate Requirements:
Candidates should have strong practical experience in enterprise data engineering and cloud architecture.
The ideal candidate should be comfortable designing conceptual, logical, and physical data models and leading implementation of modern cloud-based data platforms.
🎯 Key Responsibilities
- ✓ Design and drive end-to-end Data & Analytics architecture.
- ✓ Lead enterprise data platform architecture across GCP and Azure.
- ✓ Design conceptual, logical, and physical data models.
- ✓ Design scalable cloud data platforms.
- ✓ Lead GCP data engineering implementation.
- ✓ Lead Azure data engineering implementation.
- ✓ Define data platform architecture and technology standards.
- ✓ Design data products for enterprise use cases.
- ✓ Implement modern data engineering and analytics solutions.
- ✓ Apply Data Mesh and Data Fabric concepts where appropriate.
- ✓ Establish data governance frameworks.
- ✓ Implement data quality strategies and controls.
- ✓ Establish data observability practices.
- ✓ Design event-driven data architectures.
- ✓ Work with Kafka and cloud messaging technologies.
- ✓ Guide engineering and analytics teams.
- ✓ Mentor data engineers and technical professionals.
- ✓ Review architecture and technology selections.
- ✓ Evaluate emerging data technologies.
- ✓ Participate in technical pre-sales engagements.
- ✓ Lead proof-of-concept initiatives.
- ✓ Contribute to technology strategy.
- ✓ Drive technical thought leadership.
- ✓ Collaborate with business and technology stakeholders.
- ✓ Ensure data platforms are scalable, reliable, secure, and maintainable.
💡 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 Principal 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
1. What position is available?
The position is for a Principal Data Engineer.
2. Where is the role located?
The role is based in Dehradun, Uttarakhand, with a remote option mentioned in the job posting.
3. What is the salary budget?
The advertised budget is up to ₹40 LPA.
4. What notice period is preferred?
Candidates with a notice period of 30 days or less are preferred.
5. Are immediate joiners preferred?
Yes. Immediate joiners are preferred.
6. Is GCP experience mandatory?
Yes. Strong hands-on GCP implementation experience is required.
7. Is Azure experience mandatory?
Yes. Candidates must have hands-on experience implementing solutions on both GCP and Azure.
8. What are the major GCP technologies required?
Key GCP technologies include BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, and Cloud Storage.
9. What programming and data engineering skills are required?
Strong experience with Python, SQL, Spark, data modelling, data products, and modern data architecture is required.
10. How can candidates apply?
Candidates can send their updated resume to tech.ta.support@nhrms.in and should include their Current CTC, Expected CTC, Notice Period, and Current Location.
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