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

- **Company:** Databricks
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Microsoft Azure, Big Data, Information Engineering, Data Warehousing, Software Debugging, Python (Programming Language), Online Analytical Processing, Online Transaction Processing, Performance Tuning, E2e Testing, DataOps, Security Information and Event Management, SQL Databases, Data Streaming, Performance Testing, Snowflake, Apache Spark, Data Lakes, Apache Kafka, Spark Streaming, Splunk
- **Published:** August 11, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/specialist-solutions-architect-data-engineering-and-warehousing-financial-services-usa-58897854

## About the Role

via workshops, hackathons, and conference talks Tasks * 5+ years in a technical role with deep data engineering and warehousing expertise * Hands-on experience with streaming tech (Spark Streaming, Kafka) * Experience with batch ingestion, performance tuning, and debugging complex Spark workloads * Experience migrating EDW workloads across OLAP/OLTP systems (e.g., Redshift, Snowflake, Synapse, EMR) * Knowledge of data observability, telemetry, anomaly detection, and SIEM tools (Splunk, Elastic, Sentinel) * Deep understanding of modern lakehouse architectures (Delta Lake) across AWS, Azure, or GCP * Production-level programming in SQL and at least one language (Python, Scala, or Java) * Bachelor's degree in a related field or equivalent practical experience * Willingness to travel up to 30% * Preferred: prior experience in pre-sales or post-sales technical consulting Key requirements *

## Description

Experteer Overview In this remote, customer-facing role you guide enterprise customers through cloud data engineering transformations, leveraging hands-on experience with large-scale data warehousing and lakehouse architectures. You collaborate with Solutions Architects to validate platform value through end-to-end testing and optimization, while developing domain expertise in data lakes, streaming, ingestion, and observability. You influence technical roadmaps and contribute to community adoption and pre-sales efforts. Compensation / Benefits * Provide technical leadership to build, scale, and optimize big data and data warehousing workloads * Architect production-ready pipelines and demonstrate platform value through performance testing and optimization * Develop deep domain expertise in data lake architectures, streaming, ingestion workflows, and data observability * Support pre-sales engagements with custom POCs, workload sizing, and architecture designs * Drive community adoption via workshops, hackathons, and conference talks Tasks * 5+ years in a technical role with deep data engineering and warehousing expertise * Hands-on experience with streaming tech (Spark Streaming, Kafka) * Experience with batch ingestion, performance tuning, and debugging complex Spark workloads * Experience migrating EDW workloads across OLAP/OLTP systems (e.g., Redshift, Snowflake, Synapse, EMR) * Knowledge of data observability, telemetry, anomaly detection, and SIEM tools (Splunk, Elastic, Sentinel) * Deep understanding of modern lakehouse architectures (Delta Lake) across AWS, Azure, or GCP * Production-level programming in SQL and at least one language (Python, Scala, or Java) * Bachelor's degree in a related field or equivalent practical experience * Willingness to travel up to 30% * Preferred: prior experience in pre-sales or post-sales technical consulting Key requirements *


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