Senior Solution Architect – Data & AI | Databricks
Location: Hyderabad
Work Mode: Hybrid (3 days onsite in a week)
Role Summary
We are looking for a Senior Solution Architect – Data & AI with strong expertise in Databricks, Data Engineering, AI/ML, and cloud architecture. The ideal candidate should have enterprise architecture experience along with a Databricks Champion, FDE, Field Engineer, or similar customer-facing technical background.
Key Responsibilities
- Design end-to-end Data & AI architectures across AWS, Azure, and/or GCP.
- Lead architecture for Databricks, Lakehouse, Data Engineering, ML/AI, and analytics solutions.
- Develop reference architectures, solution blueprints, PoCs, and architecture decision documents.
- Partner with customers, business stakeholders, data scientists, and engineering teams to translate business needs into scalable solutions.
- Drive ML/AI lifecycle, MLOps, data governance, security, observability, and platform reliability.
- Lead technical workshops, solution presentations, PoCs, and pre-sales activities.
- Mentor engineering and architecture teams on modern Data & AI practices.
Architecture Governance
- Define and evolve enterprise Data & AI architecture principles, standards, reference patterns, and decision frameworks, including Architecture Decision Records and architecture review processes.
Responsible AI
- Establish and drive Responsible AI practices covering model fairness, bias detection, explainability, risk assessment, and alignment with AI governance frameworks.
FinOps / Cost Governance
- Own continuous cost optimization and FinOps practices for data and AI platforms, ensuring sustainable unit economics and right-sizing of workloads.
Required Qualifications
- 13+ years of overall technology experience with 7–8+ years in Solution/Enterprise Architecture or technical leadership.
- Strong experience with Databricks, Data Engineering, Lakehouse, Spark, Delta Lake, and ML/AI platforms.
- Strong knowledge of Python/Scala/Java and SQL.
- Experience with AWS/Azure/GCP and modern data technologies such as Kafka, Airflow, dbt, and MLflow.
- Strong understanding of Generative AI, RAG, LLMs, MLOps, and AI governance.
- Experience as a Databricks Champion, FDE, Field Engineer, Solution Architect, or similar customer-facing technical role.
- Excellent communication, stakeholder management, architecture, and technical leadership skills.
- Lead and mentor the engineering teams, workforce planning
Preferred
- Databricks or Cloud Architecture certifications.
- Experience with Responsible AI, FinOps, data governance, and enterprise compliance.
- Experience leading customer workshops, PoCs, and large-scale Data & AI transformation programs.
