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

Databricks is a Data and AI company providing a unified platform for data engineering, analytics, and AI applications. The Specialist Solutions Architect will guide enterprise customers through cloud data engineering and warehousing transformations, architect production-ready pipelines, support technical sales engagements, and promote adoption through workshops and presentations.

Responsibilities:

• Guide Strategic Implementations: Provide technical leadership to help enterprise customers successfully build, scale, and optimize big data and large-scale data warehousing workloads
• Prove Platform Value: Architect production-ready pipelines and demonstrate the power of the Databricks Data Intelligence Platform through end-to-end performance testing, load testing, and optimization
• Deep Domain Expertise: Build expertise across specialized domains such as data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability
• Support Technical Sales: Partner with Solutions Architects on complex pre-sales engagements, including custom proofs of concept (POCs), workload sizing estimations, and custom architecture designs
• Community & Adoption: Enable adoption by leading workshops, hackathons, and conference presentations, while actively contributing to the broader Databricks community

Requirements:

• 5+ years of experience in a technical role with deep expertise across Data & Software Engineering: Hands-on experience with streaming technologies (e.g., Spark Streaming, Kafka), batch ingestion, performance tuning, and troubleshooting complex Spark workloads
• 5+ years of experience in a technical role with deep expertise across Data Applications Engineering: Experience building or supporting data-driven use cases, predictive analytics pipelines, or customer analytics platforms
• 5+ years of experience in a technical role with deep expertise across 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
• 5+ years of experience in a technical role with deep expertise across Data Observability & Security: Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools (e.g., Splunk, Elastic, Sentinel)
• Deep understanding of modern lakehouse architectures (Delta Lake, data modeling, BI integration) across major cloud platforms (AWS, Azure, or GCP)
• Production-level programming experience in SQL and at least one language among Python, Scala, or Java
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience
• Ability to hit role-specific training and technical delivery milestones within the first 6 months
• Willingness to travel up to 30% as needed
• Prior experience in a pre-sales or post-sales technical consulting role