Job Title: Senior FDE (Resident Solution Architect)
Experience: 7+ Years in Data Engineering | 10+ Years in Consulting
Employment Type: Contract
Job Description
We are seeking an experienced Senior FDE (Resident Solution Architect) to lead enterprise data engineering and analytics initiatives using the Databricks Lakehouse Platform. The ideal candidate will possess deep expertise in designing scalable data solutions, architecting cloud-native platforms, and delivering high-performance distributed data processing systems.
As a Resident Solution Architect, you will work closely with customers to define technical strategy, provide architectural guidance, optimize data platforms, and ensure the successful delivery of enterprise-scale data modernization programs.
Key Responsibilities
- Design and implement scalable, secure, and high-performance data engineering solutions on the Databricks Lakehouse Platform.
- Lead end-to-end architecture, design, and implementation of enterprise data platforms.
- Provide technical leadership and architectural guidance to customer and internal engineering teams.
- Develop and optimize distributed data processing pipelines using Apache Spark.
- Collaborate with stakeholders to understand business requirements and translate them into scalable technical solutions.
- Drive cloud-native data platform implementations across AWS, Azure, or GCP.
- Implement CI/CD pipelines and DevOps best practices for production deployments.
- Apply performance tuning and scalability optimization techniques to improve platform efficiency.
- Work closely with Data Scientists and ML teams to support MLOps implementation where required.
- Stay current with Databricks platform capabilities and recommend best practices for enterprise adoption.
Required Qualifications
- 7+ years of experience in Data Engineering, Data Platforms, and Analytics.
- 10+ years of overall consulting experience.
- Databricks Data Engineering Professional Certification (Mandatory).
- Completion of the required Databricks training and certification courses.
- Proven experience delivering 6–8+ Databricks implementation projects with hands-on development responsibilities.
- Strong expertise in distributed computing using Apache Spark, including Spark architecture and runtime internals.
- Hands-on experience with Databricks platform features and ecosystem.
- Strong understanding of CI/CD practices for production-grade deployments.
- Working knowledge of MLOps concepts and implementation.
- Experience in performance tuning and scalability optimization of large-scale data workloads.
Cloud Expertise
- Strong working knowledge of at least two of the following cloud platforms:
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Deep implementation expertise in at least one cloud platform.
Preferred Skills
- Enterprise Solution Architecture
- Data Lakehouse Architecture
- Cloud-Native Data Platform Design
- Apache Spark
- Databricks Lakehouse Platform
- Data Pipeline Modernization
- Performance Optimization
- CI/CD
- MLOps
- Stakeholder Management
- Technical Consulting
- Customer Engagement
Mandatory Skills
Databricks, Databricks Data Engineering Professional Certification, Apache Spark, PySpark, Data Engineering, Lakehouse Architecture, CI/CD, MLOps, AWS, Azure, GCP, Performance Tuning, Distributed Computing, Solution Architecture, Enterprise Data Platforms.
If you have extensive experience with Databricks, enterprise-scale data engineering, and cloud-native architecture, we'd love to hear from you.
Pay: ₹80,000.00 - ₹2,472,730.74 per month
Work Location: Remote
