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Solutions Architect- Databricks - Pune District - EXL
Description
Job Summary
Job Title: Solution Architect – Databricks
Location: Any EXL Office (India)
Work Model: Hybrid (3–4 days/week onsite)
About the Role
We are looking for a highly experienced Solution Architect – Databricks to design and deliver scalable, high-performance data solutions. This role requires strong technical depth in Databricks architecture along with the ability to engage senior stakeholders across analytics, data science, AI/ML, and business teams.
Key Responsibilities
● Design and architect end-to-end data solutions using Databricks for large-scale data platforms
● Partner closely with senior leadership (VPs, Directors, Senior Directors) across Analytics, Data Science, AI/ML, and Business teams
● Lead solution design discussions, provide architectural guidance, and drive best practices
● Architect and optimize high-performance data pipelines, ingestion frameworks, and data models ● Ensure cost optimization, scalability, governance, and performance efficiency across platforms
● Enable AI/ML readiness through semantic modeling, data governance, and optimized ingestion patterns
● Mentor technical teams and provide architectural oversight across projects
Required Skills & Experience
● 10+ years of overall experience in data management / data engineering projects
● Strong expertise in Databricks architecture, including: ○ Photon ○ Liquid Clustering ○ Spark / EMR workloads ○ Databricks Autoloader ○ AI-assisted coding ○ LLM and ML integration
● Hands-on experience with: ○ Temporal and complex ingestion pipeline patterns ○ Cross-cloud data capture ○ High-performance data modeling ○ Unified data governance ○ Cost optimization strategies
● Exposure to IoT, Geospatial data, and AdTech use cases
● Strong communication skills with proven ability to work with senior stakeholders Certifications
● Databricks Certification – Associate and Professional level Mandatory
● Solution Architect Certification – Good to Have
Nice to Have
● Experience enabling AI/ML platforms at scale
● Background in analytics-driven or consulting environments
● Experience working across multi-cloud data ecosystems
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