Architect and guide the implementation of scalable data solutions across modern cloud data platforms, including Databricks and Snowflake, leveraging best‑practice patterns and reference architectures.
Lead pre‑sales and business development efforts by assessing current‑state environments, identifying client pain points, comparing platform options, and justifying ROI for tailored data solutions.
Advise client executives (CTOs, CDOs) on data strategy, platform selection, modernization roadmaps, and enterprise‑scale architecture decisions.
Serve as the architectural authority during delivery, ensuring governance, quality, and alignment with original scope while acting as an escalation point for delivery teams.
Collaborate with cross‑functional teams, engineering, BI, platform, integration, and A, to drive innovation and enable data democratization.
Mentor and guide data practitioners, leading technical discussions and delivery execution without direct people‑management responsibilities.
Stay current on platform evolution and emerging capabilities across the cloud data ecosystem, including advancements in analytics, governance, and AI tooling.
Requirements
10+ years of experience in data engineering, data architecture, solution architecture, or related roles.
Strong hands‑on experience with modern cloud data platforms, including Databricks and/or Snowflake.
Proven ability to support pre‑sales activities, including discovery sessions, technical evaluations, demos, and proposal development.
Deep understanding of enterprise data architecture, data governance frameworks, and scalable solution design.
Experience leading or supporting platform migrations from on‑prem or legacy systems to modern cloud data platforms.
Ability to pragmatically compare data platforms (e.g., Databricks vs. Snowflake) and communicate tradeoffs, cost considerations, and ROI.
Strong client‑facing communication skills with the ability to translate complex technical concepts into clear business outcomes.