Specialist Solutions Architect - HCLS - Data Warehousing
DatabricksNortheast - United StatesPosted 24 February 2026
Job Description
FEQ227R119
As a Specialist Solutions Architect (SSA) - Data Warehousing, you will guide customers in their cloud data warehousing transformation with Databricks which span a large variety of use cases. You will be in a customer-facing role, working with and supporting Solution Architects, that requires hands-on production experience with large-scale data warehousing technologies and lakehouse architecture. SSAs help customers through evaluations and successful production planning for their business intelligence workloads while aligning their technical roadmap for the Databricks Data Intelligence Platform. As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs and establish yourself in the data warehousing specialty - including performance tuning, data modeling, winning evaluations, architecture design, and production migration planning.
The impact you will have:
Provide technical leadership to guide strategic customers to successful cloud transformations on large-scale data warehousing workloads - ranging from evaluation to architecture design to production deployment
Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization
Become a technical expert in an area such as data warehousing evaluations or helping set up successful workload migrations
Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing and performance, and tuning workloads for production
Provide tutorials and training to improve community adoption (including hackathons and conference presentations)
Contribute to the Databricks Community
What we look for:
5+ years experience in a technical role with expertise in data warehousing - such as query tuning, performance tuning, troubleshooting, data governance, debugging MPP data warehouses or other big data solutions, or migration workloads from EDWother systems
Experience with design and implementation of data warehousing technologies including relational databases, SQL, data analytics, NoSQL, MPP, OLTP, and OLAP
Deep Specialty Expertise in at least one of the following areas:
Experience scaling large analytical data workloads in the cloud that are performant and cost-effective
Maintained, extended, or migrated a production data warehouse system to evolve with complex needs, including data modeling, data governance needs, and integration with business intelligence tools
Experience migrating on-premise EDW workloads to the public cloud
Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
Production programming experience in SQL and Python, Scala, or Java
Experience with the AWS, Azure, or GCP clouds
2 years professional experience with data warehousing and big data technologies (Ex: SQL, Redshift, SAP, Synapse, EMR, OLAP OLTP workloads)
2 years customer-facing experience in a pre-sales or post-sales role
Can meet expectations for technical training and role-specific outcomes within 6 months of hire
Can travel up to 30% when needed
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility ... (truncated, view full listing at source)
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