Solutions Architect

• Design Databricks Lakehouse solutions including Delta Lake, Unity Catalog, Spark optimization, governance, and MLOps patterns.
• Build scalable ETL/ELT pipelines, real-time streaming architectures, and reusable data integration frameworks.
• Develop high-level and low-level architecture blueprints ensuring security, compliance, cost efficiency, reliability, and performance.
• Architect cloud/on-prem hybrid data platforms leveraging the full Azure ecosystem including Azure Data Lake Storage, Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Purview, and Azure DevOps.

Solution Design & Delivery

• Lead requirement discovery, translate business needs into robust architectural designs and roadmaps.
• Create HLDs, LLDs, data flow diagrams, integration patterns, deployment models, and security reference architectures.
• Oversee end-to-end delivery, guiding engineering and DevOps teams through implementation and optimization.
• Perform architecture assessments and recommend improvements for scalability, resilience, and cost savings.

Technical Leadership

• Provide thought leadership and hands-on direction to data engineering, analytics, DevOps, and platform teams.
• Establish best practices for coding, data governance, CI/CD, infrastructure automation, and environment management.
• Introduce and evaluate emerging cloud technologies, tools, and frameworks relevant to analytics and modern data platforms.

Stakeholder & Client Management

• Act as technical SME for client conversations, workshops, and executive presentations.
• Communicate complex architectural concepts clearly to both technical and non-technical audiences.
• Partner closely with business stakeholders to define solution vision, roadmap, and success metrics.

Required Skills & Experience

Technical Expertise

• 12–15 years of overall IT experience with strong focus on cloud, data engineering, and enterprise architecture.
• 5+ years of hands‑on experience architecting production solutions on Microsoft Azure.
• 5+ years’ strong experience in Databricks (Spark, Delta Lake, MLflow, Unity Catalog).
• Proficiency in Python, SQL, PySpark, and distributed data processing frameworks.
• Deep understanding of data modeling, data governance, metadata management, and modern security practices.
• Experience with CI/CD pipelines, Terraform / Azure Bicep / ARM Templates, GitOps, and end-to-end automation.
• Strong knowledge of Azure networking (VNets, NSGs, Private Endpoints), Azure Active Directory, RBAC, encryption, identity governance, and security frameworks (NIST, CIS benchmarks).