Associate Architect / Architect - Databricks

Responsibilities

• Lead enterprise pre-sales engagements, including discovery workshops, solution architecture design, technical proposals, and executive presentations to CTOs, CDOs, and engineering leadership
• Design and define modern Lakehouse architectures on Databricks, leveraging Delta Lake, Delta Live Tables, Unity Catalog, Databricks SQL, MLflow, and related platform capabilities
• Own the technical direction of delivery engagements and lead a team of 4–8 data engineers by conducting design reviews, code reviews, and enforcing quality standards
• Collaborate with account managers and practice leaders to qualify opportunities, estimate effort, define delivery approaches, and support commercial proposals
• Assess customer data platforms, identify capability gaps, and develop migration or modernization roadmaps
• Establish governance, security, and compliance frameworks, including data lineage, auditability, access controls, and data quality practices
• Develop reusable accelerators, reference architectures, delivery frameworks, and best practices to improve delivery efficiency and consistency
• Represent the organization as a Databricks and Lakehouse subject matter expert at customer engagements, partner forums, industry events, and technical communities
• Mentor and coach data engineers and architects, contributing to capability development across the practice

Requirements

• 10+ years of hands-on experience in data engineering and data platform development
• 5+ years of production experience with Databricks, including Unity Catalog, Delta Lake, Spark Structured Streaming, Databricks Workflows, and Databricks SQL
• Proven experience designing and delivering enterprise-scale Lakehouse solutions supporting large-scale data environments and governance requirements
• Strong programming skills in Python and/or Scala for Spark-based workloads, with advanced SQL proficiency
• Experience working directly with enterprise customers in consulting, professional services, or system integration environments
• Demonstrated ability to lead workshops, create Statements of Work (SOWs), define solution architectures, and engage senior business and technology stakeholders
• Deep understanding of data governance, security, lineage, auditability, and regulatory compliance within modern data platforms
• Databricks Certified Data Engineer Professional and/or Databricks Certified Associate Developer for Apache Spark certification
• Experience implementing Databricks across AWS, Azure, and GCP environments
• Familiarity with the broader data ecosystem, including dbt, Fivetran, Tableau, Power BI, and related technologies
• Experience with Databricks Feature Store, MLflow, and ML-integrated data engineering workflows
• Prior experience in a Senior Architect, Principal Architect, or similar leadership role within a consulting organization, systems integrator, or Databricks partner
• Contributions to the data engineering community through technical blogs, conference presentations, open-source projects, or thought leadership content