Specialist Solutions Architect - Data Engineering & Warehousing (Financial Services)

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. The Impact You Will Have • 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 • Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain • 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 What We Look For • 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role in the following areas: • 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: Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems; advanced query tuning, governance, and MPP debugging • [Nice to have] Data Observability & Security: Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools (e.g., 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 • Excellent communication skills — able to translate complex architectures into business value for both technical and executive audiences • 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 Nice to Have • 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.) Interview Process Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Presentation → Reference Check 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 for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $180,000—$247,500 USD 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. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employm