We are seeking an accomplished technology executive to serve as Chief Technology Officer for our Databricks Data & AI consulting practice. As the senior technical authority for Databricks and the public voice of the practice, you will guide clients through data strategy, architecture and migration to Databricks, lead the technical side of pursuits, own the Databricks relationship, and build the practice's assets and market presence. Reporting to the CEO, you will partner with client executives, our account and delivery leaders, Databricks' field teams, and industry analysts. Success is measured by: Client outcomes: successful migrations and data and AI capabilities in production Practice growth: pipeline influenced, deals won and reusable assets in use Databricks channel and market presence: co-sell pipeline, partner program standing, and analyst and media visibility Req# 1112776496 Responsibilities Shape Client Data & AI Strategy: Advise client executives on multi-year data and AI platform strategy, target-state architecture, governance and AI readiness, and set the practice's vision and offerings for AI modernization, agentic analytics and advanced analytics Set Architecture & Engineering Standards: Define reference architectures and standards for Lakehouse and medallion architecture, Unity Catalog governance, Lakeflow pipelines and Mosaic AI, together with production-grade practices for CI/CD, MLOps, FinOps and the production release cycle Lead Strategic Pursuits: Own the technical side of major Databricks opportunities, from discovery workshops and assessments to solution design, effort estimation, RFP responses, SOW shaping and executive presentations, and act as technical reviewer and escalation point across engagements Drive Legacy Modernization: Lead the design of migration programs from legacy data warehouses and ETL platforms to Databricks, and build the practice's migration toolkit of assessment templates, conversion accelerators and reconciliation frameworks Own the Databricks Partnership: Lead the technical relationship with Databricks, including co-selling, joint go-to-market and roadmap briefings, and grow the practice's standing in the Databricks partner program alongside AWS, Azure and GCP relationships Build the Practice & Market Presence: Create reusable assets and solution offerings, lead public relations and analyst relations as the practice's primary technical spokesperson, and represent EPAM at conferences, webinars and Databricks community events Requirements Executive Background: 10+ years of progressive technology leadership, including 5+ years as a CTO, VP Engineering, Chief Architect or equivalent, with consulting, systems-integrator or partner-services experience and a proven ability to influence and align senior technical leaders across teams Deep Databricks Expertise: Hands-on experience designing and delivering enterprise-scale production systems on Databricks (Lakehouse, Delta Lake, Lakeflow, structured streaming, Unity Catalog, multi-workspace or multi-cloud deployments), with the ability to dive into the detail of every step: reviewing designs, data models, code, performance and cost Legacy Migration Track Record: Demonstrated success leading migrations from legacy data warehouses and ETL tools (e.g., Teradata, Netezza, Oracle, SQL Server, Informatica, SSIS) to Databricks, through assessment, wave planning, code conversion, reconciliation and cutover, with the judgement to validate estimates AI & Advanced Analytics: Track record of shipping production ML and generative AI systems, and experience with AI modernization, agentic analytics and advanced analytics (e.g., Agent Bricks, AI/BI Genie, RAG, predictive models) delivering measurable business impact Engineering Excellence: Strong command of Apache Spark internals, at least one major cloud (AWS, Azure, GCP), CI/CD with Databricks Asset Bundles, infrastructure-as-code, MLOps and FinOps, plus hands-on Python/PySpark and SQL, and experience establishing governance and security in regulated industries Market & Ecosystem Knowledge: Ability to position Databricks credibly against Snowflake, Microsoft Fabric, BigQuery and AWS-native analytics, and solid knowledge of interoperability (Delta Lake, Iceberg, UniForm, Delta Sharing) and the surrounding BI, orchestration and streaming ecosystem Certifications: A Databricks professional- or architect-level credential (e.g., Data Engineer Professional, Platform Architect accreditation), or commitment to obtain one within 6 months; ML/GenAI certifications, partner accreditations, or Databricks Champion/MVP status are a strong plus Executive Communication & Thought Leadership: Exceptional storytelling, presentation and executive advisory skills, with experience representing an organization to board-level stakeholders, industry analysts (e.g., Gartner, Forrester, Everest Group, ISG) and the media
