FEQ327R691 As a Data Engineering and Warehousing Specialist Solutions Architect (SSA), you will lead the advanced technical strategy for your customers — owning complex architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are further developing a technical specialization and are recognized within the Field Engineering team for depth in the specific domain.
This position can be remote. Own the end-to-end technical strategy for your accounts, from discovery through production deployment and consumption growth
Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering and real-time analytics
Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions
Orchestrate cross-functional resources (DSAs, SAs, Partners) to deliver comprehensive solutions for complex customer needs
Influence product direction by providing structured feedback on customer requirements and competitive gaps
Data and Software Engineering: Deep hands-on experience with Apache Spark™ ecosystem (Spark Core, Spark SQL, Spark Streaming), message queues (e.g., Kafka), batch ingestion, performance tuning, and troubleshooting complex Spark workloads
~ Data Applications Engineering: Experience building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms
~ Data Warehousing & Migration: legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems; Nice to have] Data Observability & Security: Splunk, Elastic, Sentinel)


Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis
Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
Track record of driving platform adoption and consumption growth within accounts
Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
Willingness to travel up to 30% as needed
Databricks certifications (Data Engineer, ML, Platform)
Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
Background in a data/AI company or cloud provider
Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)
Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Presentation → Reference Check
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 for annual performance bonus, equity, and the benefits listed above. Local Pay Range
$About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
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