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Role Description

As a Databricks Practice Lead, you are a strategic and hands-on expert in modern data architecture, focused on helping organizations unlock the full value of their data. You thrive in client-facing roles, partnering with executives such as CTOs and CDOs to guide enterprise-scale transformations and platform decisions. You bring deep expertise in the Databricks Lakehouse Platform and its evolving ecosystem, offering clarity to complex challenges including migrations, governance, and AI enablement. You combine technical depth with business acumen, supporting pre-sales engagements by evaluating client needs, comparing platforms like Snowflake and Databricks, and building ROI-driven solution strategies. You lead cross-functional teams without direct reports, mentor others, and ensure solutions are delivered as designed and aligned with strategic goals. You work effectively in dynamic environments, communicate clearly across technical and business audiences, and consistently deliver practical, high-impact outcomes.

Day-to-Day

• Architect and implement scalable data solutions using the Databricks Lakehouse Platform, including Medallion architecture, streaming integration, and ACID-compliant designs.
• Lead pre-sales and business development efforts by assessing current-state environments, identifying client pain points, comparing technologies, and justifying ROI for tailored solutions.
• Advise client executives (CTOs, CDOs) on strategic data initiatives, platform evolution, and enterprise-scale architecture decisions.
• Ensure governance and alignment of delivered solutions with original scope, serving as the escalation point for delivery teams.
• Collaborate across cross-functional teams, such as engineering, BI, platform, integration, and AI, to drive innovation and data democratization.
• Mentor and guide data teams, leading discussions and technical delivery without formal people management responsibilities.
• Stay current on product evolution, including Lakehouse Monitoring, Lake Designer, Delta Sharing, Mosaic AI, and Matrix.

Qualifications

• 7+ years of experience in data engineering, solution architecture, or related roles.
• Hands-on expertise with Databricks Lakehouse Platform and cloud-based data technologies.
• Experience supporting pre-sales activities such as discovery sessions, technical demos, and proposal development.
• Strong background in enterprise data architecture, governance frameworks, and scalable solution design.
• Experience with platform migrations including Snowflake, Informatica, and on-prem systems.
• Ability to compare cloud platforms pragmatically and provide cost and ROI analysis (e.g., Snowflake vs Databricks) during pre-sales engagements.
• Proven client-facing skills with the ability to lead strategic conversations and translate technical solutions into business impact.
• Excellent communication and collaboration skills with a transparent, humble, and adaptable approach.