We are looking for experienced Senior FDEs / Resident Solution Architects with strong expertise in Databricks, Data Engineering, Apache Spark, and Cloud Data Platforms.
The successful candidate will work closely with enterprise customers and engineering teams to design, implement, optimize, and modernize large-scale data platforms using the Databricks Lakehouse Platform.
This is a hands-on technical consulting and architecture role requiring strong experience in enterprise data engineering, cloud-native architectures, distributed computing, and customer engagement.
Key Responsibilities
- Design and implement scalable, secure, and high-performance data solutions using Databricks Lakehouse.
- Lead end-to-end architecture, design, development, and implementation of enterprise data platforms.
- Provide technical leadership and architectural guidance to customers and engineering teams.
- Design and optimize large-scale data pipelines using Apache Spark.
- Understand business and technical requirements and translate them into scalable data solutions.
- Drive cloud-native data platform implementations across AWS, Azure, or GCP.
- Implement CI/CD pipelines and DevOps best practices for production deployments.
- Perform performance tuning and scalability optimization of large-scale data workloads.
- Work with Data Science and ML teams on MLOps initiatives where required.
- Advise customers on Databricks architecture, platform capabilities, and implementation best practices.
- Participate in technical discussions, solution workshops, design reviews, and customer engagements.
- Ensure successful delivery of enterprise-scale data modernization initiatives.
Required Qualifications
- 7+ years of experience in Data Engineering, Data Platforms, or Analytics.
- 10+ years of overall consulting experience.
- Databricks Data Engineering Professional Certification – Mandatory.
- Completion of required Databricks training and certification programs.
- Proven experience delivering 6–8+ Databricks implementation projects with significant hands-on development responsibilities.
- Strong expertise in Apache Spark, including Spark architecture, execution model, and runtime concepts.
- Hands-on experience with Databricks platform features and the broader Databricks ecosystem.
- Strong understanding of CI/CD and DevOps practices for production data platforms.
- Working knowledge of MLOps concepts and implementation.
- Strong experience in performance tuning and scalability optimization of large-scale data workloads.
- Excellent communication, problem-solving, consulting, and stakeholder management skills.
Cloud Expertise
Candidates should have:
- Strong working knowledge of at least two of the following cloud platforms:
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Deep hands-on implementation expertise in at least one major cloud platform.
Preferred Skills
- Enterprise Solution Architecture
- Databricks Lakehouse Architecture
- Cloud-Native Data Platform Design
- Apache Spark
- Data Pipeline Modernization
- Performance Optimization
- CI/CD & DevOps
- MLOps
- Technical Consulting
- Customer Engagement & Stakeholder Management
Why Join Us?
- Work on large-scale enterprise data modernization programs.
- Engage with global customers and leading engineering teams.
- Work with the latest Databricks and cloud technologies.
- Take ownership of strategic technology and architecture decisions.
- Opportunity to work on complex, enterprise-scale data platforms.
Pay: ₹2,200,000.00 - ₹2,800,000.00 per year
Work Location: Remote
