Senior Databricks Consulting Engineer
Summary
Senior consultant designs and implements Databricks Lakehouse platforms for enterprises, advising on Spark, Delta Lake, and AI workloads while mentoring teams and driving adoption.
The Role
As a Senior Databricks Consulting Engineer, you will serve as a trusted technical advisor and strategic partner to enterprise customers. You will guide organizations through their data and AI transformation journeys, helping them design, implement, and optimize modern data platforms built on Databricks.
You will combine deep technical expertise with strong stakeholder management skills to ensure customers realize measurable value from their Databricks investments. Working alongside client teams, executives, engineers, and Ultra Tendency consultants, you will lead architecture decisions, promote best practices, and drive successful adoption of the Databricks Lakehouse Platform.
This is a highly customer-facing role requiring both hands-on technical capability and executive-level communication skills.
Key Responsibilities
Customer Advisory & Architecture
- Act as the primary technical advisor for strategic Databricks customers.
- Design and review scalable data, analytics, and AI architectures leveraging the Databricks Lakehouse Platform.
- Lead architecture workshops, solution design sessions, and technical roadmap discussions.
- Translate business requirements into technical solutions and implementation plans.
- Advise customers on platform modernization, cloud migration, data governance, and AI initiatives.
Solution Delivery & Optimization
- Support the successful implementation and adoption of Databricks solutions.
- Review data engineering, analytics, machine learning, and GenAI workloads for scalability, performance, security, and cost optimization.
- Identify and resolve technical blockers during customer engagements.
- Drive architectural best practices for data pipelines, Lakehouse design, Unity Catalog, governance, and platform operations.
Technical Leadership
- Serve as a subject matter expert on Databricks capabilities and emerging data & AI technologies.
- Mentor customer teams and Ultra Tendency consultants on architecture patterns and best practices.
- Deliver executive presentations, technical workshops, and enablement sessions.
- Contribute to reusable assets, reference architectures, and practice development initiatives.
Business Development Support
- Partner with sales and account teams during strategic customer engagements.
- Support technical discovery, solution positioning, and proposal development.
- Provide architecture guidance during pre-sales and proof-of-concept activities.
- Identify opportunities for platform expansion and increased customer value.
Required Qualifications
- 7+ years of experience in data engineering, cloud architecture, analytics, or related fields.
- 3+ years working with Databricks in enterprise environments.
- Strong expertise in modern data platform architecture and cloud-native solutions.
- Hands-on experience designing and implementing Lakehouse architectures.
- Strong knowledge of:
- Databricks Data Intelligence Platform
- Apache Spark
- Delta Lake
- Unity Catalog
- Data Governance & Security
- Data Warehousing and Lakehouse Design
- ETL/ELT Architectures
- Data Modeling
- Experience with at least one major cloud platform:
- Microsoft Azure (preferred)
- AWS
- Google Cloud Platform
- Proficiency in:
- Python
- SQL
- Spark
- Experience engaging with executive stakeholders and technical leadership teams.
- Excellent communication and presentation skills
Preferred Qualifications
- Databricks certifications such as:
- Databricks Certified Data Engineer Professional
- Databricks Certified Solutions Architect
- Databricks Certified Machine Learning Professional
- Experience with:
- Generative AI and LLM solutions
- MLflow
- MLOps
- Data Governance frameworks
- Data Mesh architectures
- Real-time and streaming data platforms
- Experience in consulting or professional services environments.
- Additional language skills are desirable
What Success Looks Like
- Customers successfully adopt and scale Databricks solutions.
- Complex technical challenges are resolved quickly and effectively.
- Executive stakeholders view you as a trusted advisor.
- Best practices are consistently applied across customer environments.
- Customer satisfaction, platform utilization, and business outcomes improve measurably.