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

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

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.

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
• 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
• Experience building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms
• Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems; advanced query tuning, governance, and MPP debugging
• Strong coding proficiency in Python and SQL — ability to 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)
• Proven ability to lead architecture discussions with senior technical stakeholders (whiteboarding, design reviews, 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
• 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

• Data observability & security experience: Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools (e.g., Splunk, Elastic, Sentinel)
• Databricks certifications (Data Engineer, ML, Platform)
• Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse)
• Background in a data/AI company or cloud provider
• Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)