Specialist Solutions Architect - Data Engineering & Warehousing

Databricks

Posted 1mo ago

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Guide strategic implementations for enterprise customers building and scaling big data and data warehousing workloads
Architect production-ready pipelines and demonstrate platform value through performance testing, load testing, and optimization
Build expertise in data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability
Support technical sales by partnering with Solutions Architects on pre-sales engagements, POCs, workload sizing, and architecture designs
Enable adoption by leading workshops, hackathons, and conference presentations, and contributing to the Databricks community

5+ years in a technical role with deep expertise in data and software engineering
Deep hands-on experience with Apache Spark ecosystem (Spark Core, Spark SQL, Spark Streaming)
Experience with message queues (e.g., Kafka), batch ingestion, performance tuning, and troubleshooting 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
Familiarity with telemetry, high-velocity log ingestion, anomaly detection, and SIEM tools (e.g., Splunk, Elastic, Sentinel)
Deep understanding of modern lakehouse architectures (Delta Lake, data modeling, BI integration) across AWS, Azure, or GCP
Production-level programming in SQL and at least one of 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

Skills