Databricks Resident Solution Architect

Role Description

As a Databricks Resident Solution Architect, you are a senior, hands‑on architect responsible for designing, guiding, and operationalizing modern cloud data platforms built on the Databricks Lakehouse. You bring deep expertise in Databricks, Spark, and large‑scale data engineering, and you are comfortable operating within complex, regulated enterprise environments. You thrive in resident architect engagements, working closely with client stakeholders to establish strong architectural foundations, governance standards, and long‑term platform strategies. You excel at translating business objectives into secure, scalable technical designs and guiding teams through platform adoption, analytics enablement, and AI readiness. You are confident in acting as a technical authority while collaborating effectively across business and engineering teams.

Qualifications

• 10+ years of overall experience in data engineering, data architecture, or analytics engineering roles.
• 5+ years of hands‑on experience with Databricks, including Delta Lake, Unity Catalog, Workflows/Jobs, and Lakehouse architecture.
• Databricks Professional Certification (MANDATORY).
• Strong expertise in Apache Spark (PySpark preferred), Python, and advanced SQL.
• Proven experience designing and implementing production‑grade, large‑scale data pipelines.
• Hands‑on experience with at least one major cloud platform (Azure preferred, AWS or GCP acceptable).
• Experience with data modeling, Medallion architecture, and enterprise data platform design.
• Familiarity with CI/CD pipelines, infrastructure automation tools (e.g., Terraform), and Agile delivery practices.
• Strong communication and stakeholder‑facing skills, with experience operating in regulated enterprise environments.

Requirements

• Architect and guide implementation of Databricks‑based data platforms, leveraging Lakehouse and Medallion architecture best practices.
• Provide hands‑on technical leadership across data engineering, analytics, and AI‑enabled use cases using Databricks.
• Define and enforce data governance, security, and access control standards using Databricks Unity Catalog and enterprise data management principles.
• Enable and support AI/ML workloads, including ML pipelines and model lifecycle integration within the Databricks ecosystem.
• Optimize platform performance, scalability, and cost efficiency with a FinOps‑oriented mindset.
• Collaborate closely with business leaders, architects, and engineering teams to align platform capabilities with enterprise data and analytics needs.
• Serve as a resident technical authority, providing architectural guidance, mentoring teams, and ensuring solution quality and consistency.