Accountabilities

Data Architecture & Engineering: Design, develop, and oversee large-scale enterprise data architecture solutions using Databricks and its ecosystem, including Delta Lake, Delta Live Tables, Unity Catalog, and Apache Iceberg.
Databricks Center of Excellence: Contribute to the development and growth of the Databricks practice by establishing technical standards, sharing expertise, promoting best practices, and leading strategic platform initiatives.
Technical Leadership: Provide architectural direction and technical guidance to data architects and engineering teams, ensuring solutions align with client objectives, business requirements, scalability, and performance expectations.
Client Advisory & Digital Transformation: Act as a trusted technical advisor to clients, guiding them through data strategy development, digital transformation, and the adoption of modern cloud-based data platforms.
Pre-Sales & Business Development: Lead complex Databricks pre-sales engagements as a Solution Lead or Lead Architect. Develop tailored technical proposals, solution architectures, statements of work (SOWs), and strategic recommendations based on client requirements.
Project Delivery & Modernization: Lead large-scale Databricks implementation, migration, and modernization engagements, overseeing delivery teams of data architects and engineers to ensure successful project outcomes.
Migration Strategy: Drive the transformation of legacy data warehouses into modern Databricks Lakehouse architectures, ensuring efficient migration approaches, platform optimization, and business continuity.
Project & Risk Management: Oversee project planning, budgeting, deliverables, timelines, dependencies, and risks while maintaining alignment with client expectations and executive stakeholders.
Innovation & Technology Strategy: Identify emerging technologies, tools, and architectural approaches in data engineering, cloud platforms, and AI/ML to develop future-ready solutions aligned with client needs.
Practice Growth & Market Development: Collaborate with data leadership teams across sales, recruitment, account management, consulting, and operations to expand market presence and strengthen client relationships.
Mentorship & Knowledge Sharing: Mentor technical professionals, develop engineering capabilities, and promote a culture of innovation, accountability, collaboration, and continuous learning.
Business Value & Client Outcomes: Ensure that technical decisions and architectural recommendations deliver measurable business value, improve operational efficiency, and strengthen clients' competitive positioning.

Requirements

At least 10 years of professional experience in data engineering, data architecture, or related technology disciplines.
Minimum of 6 years of extensive hands-on experience with Databricks, including Delta Lake, Delta Live Tables, and Unity Catalog.
Strong expertise in designing and implementing enterprise-scale data architectures and modern data engineering solutions.
Deep understanding of Databricks platform capabilities, including data engineering, governance, security, and Lakehouse architecture.
Mastery of Big Data platforms, cloud data warehouses, and object-oriented programming principles.
Strong knowledge of NoSQL databases, container management technologies, and AI/ML tools.
Demonstrated experience designing and delivering data and AI platform solutions that address complex business requirements and generate measurable business value.
Proven experience leading large-scale data migration and modernization initiatives, particularly transforming legacy data warehouses into Databricks Lakehouse platforms.
Experience managing multiple complex Databricks implementation and delivery projects, including technical leadership and team coordination.
Ability to translate business needs into customized data platform architectures and scalable technical solutions.
Experience leading pre-sales and business development activities, including solution design, technical proposals, client presentations, and SOW development.

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