Experience 7+ Years in Data Engineering | 10+ Years in Consulting
Role Overview
We are seeking an experienced Senior 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 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 Qualified 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 major cloud platforms:
o Microsoft Azure o Amazon Web Services (AWS)
o 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
- Performance optimization
- Data pipeline modernization
- Stakeholder management
- Technical consulting and customer engagement
Why Join Us?
- Work on large-scale enterprise data modernization initiatives.
- Collaborate with industry-leading architects and engineering teams.
- Drive innovation using the latest Databricks and cloud technologies.
- Influence strategic technology decisions for global customers.
📌 Databricks Architect (India)
🏢 Celebal Technologies
📍 India
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