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

The role

You will lead technical strategy for customers by owning complex architecture discussions and driving platform adoption. You will design scalable solutions spanning data engineering and real-time analytics to position Databricks as a foundation for data and AI strategy.

What you will do

• Own end-to-end technical strategy for accounts from discovery through production deployment.
• Lead complex architecture discussions for scalable, production-grade solutions.
• Serve as a trusted technical advisor to customer architects, engineering leads, and Directors.
• Drive technical wins by demonstrating differentiation through custom-built solutions.
• Develop and declare an emerging technical specialization.
• Orchestrate cross-functional resources to deliver solutions for complex customer needs.
• Influence product direction with feedback on customer requirements and competitive gaps.

Required qualifications

• 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role in Data and Software Engineering, Data Applications Engineering, or Data Warehousing & Migration.
• Deep hands-on experience with Apache Spark ecosystem (Spark Core, Spark SQL, Spark Streaming), message queues, 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 across OLAP/OLTP systems.
• Advanced query tuning, governance, and MPP debugging.
• Strong coding proficiency in Python and SQL.
• Deep expertise in distributed data systems architecture.
• Proficient on the Databricks Platform or ability to achieve proficiency rapidly.
• Ability to lead architecture discussions with senior technical stakeholders.
• Experience with production deployments on public cloud (AWS, Azure, or GCP).
• Track record of driving platform adoption and consumption growth.
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline or equivalent experience.

Nice to have

• Data Observability & Security: Telemetry, high-velocity log ingestion, anomaly detection, and familiarity with SIEM tools.
• 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.).

Benefits

• Annual performance bonus
• Equity

Before you apply

• Recruiter Screen
• Hiring Manager Screen
• Design and Architecture Interview
• Live Coding Assessment
• Presentation

About the company

Databricks is the Data and AI company. More than 20,000 organizations worldwide rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.