Sr. Specialist Solutions Architect - Data Engineering & Warehousing

Databricks is the data and AI company, and they are seeking a Sr. Specialist Solutions Architect - Data Engineering & Warehousing to guide customers through cloud data engineering transformations. In this role, you will provide technical leadership, architect production-level data pipelines, and assist in customer implementations of big data projects.

Responsibilities:

• Provide technical leadership to guide strategic customers to successful implementations on big data projects and large-scale data warehousing workloads
• Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization
• Architect production-level data pipelines, including end-to-end pipeline load performance testing and optimization
• Become a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows
• Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content, estimating workload sizing, and custom architectures
• Provide tutorials and training to improve community adoption (including hackathons and conference presentations)
• Contribute to the Databricks Community

Requirements:

• 8+ years of experience in a technical role with deep expertise across the following areas: Software / Data Engineering: Hands-on experience with data ingestion, streaming technologies (e.g., Spark Streaming, Kafka), performance tuning, troubleshooting, and debugging Spark or other big data solutions
• Data Applications Engineering: Experience building data-driven use cases, such as risk modeling, fraud detection, and customer lifetime value (LTV)
• Data Warehousing: Advanced query tuning, troubleshooting, data governance, and debugging MPP data warehouses or big data solutions. Experience migrating workloads from EDW systems (e.g., traditional SQL, Redshift, Snowflake, Synapse, EMR) across OLAP & OLTP workloads
• Data Observability: Experience with SIEM tools (e.g., Splunk, Elastic, Sentinel), telemetry/high-velocity log ingestion, and anomaly detection
• Proven track record of maintaining, scaling, and extending production data systems to evolve with complex business needs
• Deep expertise across multiple core data engineering domains, including: Designing and scaling cost-efficient, high-performance data workloads (ETL/ELT, analytics) in cloud environments
• Building and migrating large-scale data pipelines, including batch, CDC (Change Data Capture), and streaming ingestion
• Migrating on-premises or Hadoop-based data systems to modern cloud platforms (AWS, Azure, GCP)
• Developing and managing modern lakehouse and warehouse systems, including Delta Lake technologies, data modeling, governance, and BI integration
• Production programming experience in SQL and at least one of the following: Python, Scala, or Java
• Degree or Equivalent: Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent professional experience
• 3+ years of customer-facing experience in a pre-sales or post-sales technical role
• Ability to meet expectations for technical training and role-specific milestones within 6 months of hire
• Willingness to travel up to 30% as needed
• Strong familiarity with cloud infrastructure providers (AWS, Azure, or GCP) is highly desirable