Solutions Architect- Databricks

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