Job Overview
| Particulars | Details |
|---|---|
| Position | Senior Data Engineer |
| Company | MetrixIT Solutions |
| Location | MetrixIT Solutions |
| Job Type | Remote |
| Experience | 6 - 8 years |
| Category / Department | Data Scientist |
| Application Mode |
🏢 About MetrixIT Solutions
Company Overview
MetrixIT Solutions is a global IT consulting and software solutions company headquartered in Charlotte, North Carolina. Since 2017, the company has been helping organizations accelerate digital transformation through innovative technology solutions, expert consulting, and highly skilled engineering professionals.
Our Mission
To deliver reliable, innovative, and cost-effective technology solutions that help organizations improve operational efficiency, accelerate growth, and achieve long-term business success.
Our Vision
To become a trusted global technology partner by delivering scalable IT solutions, exceptional consulting services, and innovative digital transformation strategies.
Core Values
• Innovation
• Customer Success
• Quality Delivery
• Transparency
• Integrity
• Collaboration
What Makes MetrixIT Solutions Different
MetrixIT Solutions combines technical expertise, customized technology solutions, and customer-focused consulting to help businesses solve complex challenges while maintaining high quality standards, transparent execution, and rapid project delivery.
Work Culture
The company promotes innovation, effective communication, continuous learning, and collaborative problem-solving while empowering employees to build impactful technology solutions.
MetrixIT Solutions
8832 Blakeney Professional Drive, Suite 205
Charlotte, NC 28277, USA
💡 Editor's Note / Preparation Tip
Resume Preparation
• Highlight enterprise data engineering and streaming projects.
• Showcase experience with Databricks, PySpark, Kafka, and Delta Lake.
• Include cloud platform experience and measurable project achievements.
• Mention ETL/ELT frameworks, orchestration tools, and data modeling expertise.
• Optimize your resume with relevant data engineering keywords for ATS.
Interview Preparation
• Revise Spark architecture, PySpark optimizations, and Kafka internals.
• Review Databricks, Delta Lake, and Lakehouse architecture concepts.
• Prepare SQL optimization and distributed data processing scenarios.
• Understand cloud-native data engineering best practices.
• Be ready to discuss large-scale production data engineering projects.
Professional Career Tips
• Build expertise in real-time streaming and event-driven architectures.
• Stay updated with the latest Databricks and Apache Spark features.
• Learn advanced cloud-native data engineering services.
• Strengthen data modeling and performance optimization skills.
• Develop strong system design knowledge for large-scale data platforms.
📝 Job Description
🚀 We're Hiring: Senior Data Engineer (Databricks / PySpark / Kafka) | MetrixIT Solutions
Are you passionate about building scalable real-time data platforms and modern streaming solutions? MetrixIT Solutions is looking for an experienced Senior Data Engineer with expertise in Databricks, PySpark, Apache Kafka, and Lakehouse architectures. If you enjoy designing high-performance data pipelines and working with cloud-based big data technologies, this remote opportunity could be your next career move.
📌 Position Details
Position: Senior Data Engineer – Streaming
Company: MetrixIT Solutions
Location: Remote
Work Mode: Remote
Employment Type: Full-Time (Employment type not specified in the original post)
Experience: 6–8 Years
Qualification: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field (Preferred)
⭐ Preferred Skills
✔ Lakehouse Architecture
✔ Real-Time Streaming Pipelines
✔ Cloud-Native Data Platforms
✔ Performance Optimization
✔ Remote Team Collaboration
🎯 Candidate Requirements
• 6–8 years of hands-on experience in Data Engineering.
• Strong expertise in PySpark and Apache Spark.
• Extensive experience with Apache Kafka and streaming architectures.
• Proven experience working with Databricks and Delta Lake.
• Strong knowledge of SQL and distributed computing concepts.
• Experience with AWS, Azure, or GCP cloud platforms.
• Familiarity with ETL/ELT frameworks, orchestration tools, and data modeling.
• Excellent analytical, troubleshooting, and communication skills.
• Ability to work independently in a remote environment.
🌟 Why Join MetrixIT Solutions?
✅ Fully Remote work opportunity.
✅ Work on enterprise-scale real-time data platforms.
✅ Exposure to modern Lakehouse and streaming technologies.
✅ Opportunity to collaborate with experienced global engineering teams.
✅ Innovative and technology-driven work environment.
✅ Professional growth through challenging data engineering projects.
✅ Supportive culture focused on continuous learning and technical excellence.
📩 How to Apply
Interested candidates can share their updated resume at:
Know someone who would be a great fit? Tag them in the comments or share this opportunity with your network.
🎯 Key Responsibilities
- ✓ Design and build scalable real-time data pipelines using Apache Spark and PySpark.
- ✓ Develop and maintain streaming data solutions using Apache Kafka.
- ✓ Implement enterprise-grade Lakehouse architectures with Databricks and Delta Lake.
- ✓ Build, optimize, and maintain ETL/ELT data processing workflows.
- ✓ Design efficient SQL queries and optimize distributed data processing workloads.
- ✓ Work with cloud platforms including AWS, Azure, or Google Cloud Platform.
- ✓ Develop scalable data models and support orchestration frameworks.
- ✓ Monitor data platform performance and troubleshoot production issues.
- ✓ Collaborate with cross-functional teams to deliver reliable data engineering solutions.
💡 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 Senior 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 ₹12,00,000 - ₹25,00,000+ per annum (Senior/Lead 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
Q1. Is this a remote position?
Yes. This role is fully remote.
Q2. How much experience is required?
Candidates should have 6–8 years of experience in Data Engineering.
Q3. Which technologies are mandatory?
PySpark, Apache Spark, Apache Kafka, Databricks, Delta Lake, SQL, and cloud platform experience.
Q4. Which cloud platforms are acceptable?
Experience with AWS, Microsoft Azure, or Google Cloud Platform (GCP) is preferred.
Q5. Is streaming architecture experience required?
Yes. Hands-on experience with real-time streaming platforms and Kafka is a key requirement.
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