Databricks Practice Lead
London
Permanent
The Databricks Practice Lead is a pivotal, hands-on leadership role responsible for defining the vision, strategy, and execution capabilities of our firm's Databricks-focused consulting practice. This role requires a unique blend of technical mastery, client-facing consulting skills, practice development, and expertise in business development/pre-sales activities. You will be the internal expert and external champion for all things related to the Databricks Lakehouse Platform.
Key Responsibilities
Practice Strategy & Leadership
* Define and Own Strategy: Develop and execute a comprehensive 1-3 year strategy for the Databricks Practice, aligning with overall company goals, market trends, and Databricks' product roadmap.
* Talent Development: Lead recruitment, mentoring, and professional development for the Databricks consultant team, ensuring high-quality delivery skills across Data Engineering, Data Science, and ML Ops.
* Partnership Management: Act as the primary technical liaison and escalation point for the strategic relationship with Databricks, ensuring the practice maintains high partner status and relevant certifications.
* IP Development: Oversee the creation of reusable assets, accelerators, methodologies, and reference architectures that improve delivery efficiency and quality for clients.
Technical Delivery & Governance
* Architectural Guidance: Serve as the Executive Architect on complex, large-scale Databricks implementations (Data Warehousing, ETL/ELT, Streaming, ML Ops), providing expert oversight and quality assurance.
* Standards & Best Practices: Establish and enforce best practices for solution design, performance tuning, governance (Unity Catalog), cost optimization, and security within the Databricks Lakehouse.
* Problem Resolution: Act as the ultimate technical escalation point, utilizing deep expertise to unblock complex delivery challenges related to Spark, delta lake, cloud integration (AWS/Azure/GCP), and data governance.
Business Development & Pre-Sales
* Thought Leadership: Produce high-quality collateral (white papers, blog posts, presentations) and speak at industry events to elevate the company's reputation as a Databricks leader.
* Sales Enablement: Collaborate closely with the sales team to scope new engagements, estimate efforts, define compelling Statements of Work (SOWs), and present solution proposals to prospective clients.
* Client Advisory: Engage with C-level and senior technical stakeholders to understand business challenges and demonstrate how the Databricks Lakehouse Platform can deliver transformational value.
Required Qualifications
* Education: Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
* Experience: 8+ years of experience in data engineering, data warehousing, or software development, with a minimum of 3+ years dedicated to the Databricks Lakehouse Platform.
* Technical Mastery: Deep, demonstrable expertise in Databricks components, including Delta Lake, Spark SQL, MLflow, and Unity Catalog.
* Programming: High proficiency in at least one of the following: Python, Scala, or SQL (with a preference for PySpark/Scala).
* Cloud Fluency: Expert-level knowledge of at least one major cloud platform (AWS, Azure, or GCP) and how Databricks integrates with native cloud services (e.g., S3/ADLS/GCS, IAM/Entra ID).
* Consulting Experience: Proven experience in a consulting or client-facing capacity, managing stakeholder expectations and leading large project teams.
* Leadership: Demonstrated experience leading and mentoring a team of technical consultants or engineers.
Preferred Qualifications
* Databricks Certified Data Engineer Professional, Databricks Certified Machine Learning Professional, or equivalent advanced Databricks certifications.
* Experience with Infrastructure as Code (IaC) tools such as Terraform for deploying Databricks workspaces and related cloud infrastructure.
* Proven track record in pre-sales, generating six-figure consulting engagements.
* Experience working with real-time data streaming technologies (e.g., Kafka, Azure Event Hub, Kinesis) and Databricks Structured Streaming.
* MBA or advanced degree is a plus.