The Senior Architect will play a strategic role in designing and delivering large-scale, modern data engineering solutions using the Databricks Lakehouse platform. This position combines deep technical expertise, enterprise architecture, consulting, and business leadership to address complex data challenges and accelerate digital transformation. You will lead major data architecture initiatives, guide engineering teams, and advise clients on building scalable, secure, and high-performance data platforms. Working closely with business leaders and technical stakeholders, you will translate organizational objectives into innovative data and AI solutions. You will also contribute to business development, lead pre-sales engagements, and oversee complex migration and modernization projects. This is an exciting opportunity to shape data engineering strategy, drive technological innovation, and deliver measurable business value in a collaborative consulting environment.
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.