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Job SummaryJob 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