Specialist Solutions Architect - Data Engineering & Warehousing (Digital Native Business)

Databricks is a Data and AI company that provides the Databricks Data Intelligence Platform to organizations worldwide. The Specialist Solutions Architect will guide enterprise customers through cloud data engineering transformations, architect and optimize data engineering and warehousing workloads, support technical sales engagements, and lead adoption initiatives such as workshops and presentations.

Responsibilities:

• Provide technical leadership to help enterprise customers successfully build, scale, and optimize big data and large-scale data warehousing workloads
• Architect production-ready pipelines and demonstrate the power of the Databricks Data Intelligence Platform through end-to-end performance testing, load testing, and optimization
• Build expertise across specialized domains such as data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability
• Partner with Solutions Architects on complex pre-sales engagements, including custom proofs of concept (POCs), workload sizing estimations, and custom architecture designs
• 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: 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
• 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