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

Databricks
Texas
Workplace: RemoteFull timeUSD 180,000 - 247,500 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: bachelorsSkills: ["Technical leadership","Mentorship","Continuous learning","Technical troubleshooting","Workload optimization"]

Lead strategic enterprise customer transformations for cloud data engineering and data warehousing using the Databricks Data Intelligence Platform. Build and validate production-ready pipelines through performance/load testing and optimization, and deepen expertise across lakehouse architecture, streaming, ingestion, and data observability. Partner with Solutions Architects on complex pre-sales work such as POCs, workload sizing, and architecture designs, while driving adoption through workshops, hackathons, and technical presentations.

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FursaFursa
Databricks
Databricks
1 day ago

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

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Last checked: 6 hours agoStatus: Live

Job Summary

Lead strategic enterprise customer transformations for cloud data engineering and data warehousing using the Databricks Data Intelligence Platform. Build and validate production-ready pipelines through performance/load testing and optimization, and deepen expertise across lakehouse architecture, streaming, ingestion, and data observability. Partner with Solutions Architects on complex pre-sales work such as POCs, workload sizing, and architecture designs, while driving adoption through workshops, hackathons, and technical presentations.
Location: Texas
Workplace: Remote
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

  • •Provide technical leadership for strategic enterprise implementations to build, scale, and optimize big data and large-scale data warehousing workloads.
  • •Architect production-ready pipelines and demonstrate platform value through end-to-end performance testing, load testing, and optimization.
  • •Develop deep domain expertise across data lake architecture, high-velocity streaming, automated ingestion workflows, and data observability.
  • •Support technical sales by partnering on complex pre-sales engagements, including custom POCs, workload sizing estimations, and custom architecture designs.
  • •Enable adoption by leading workshops, hackathons, and conference presentations while contributing to the Databricks community.
Travel: Medium travel

Pay and Benefits

Salary: USD 180,000 - 247,500 annually
Equity and Bonus:Equity
Perks:Annual BonusEquity

Key Requirements

  • •5+ years of experience in a technical role with deep expertise across data and software engineering, including streaming (Spark Streaming, Kafka), batch ingestion, performance tuning, and troubleshooting.
  • •Experience building/supporting data applications such as predictive analytics pipelines or customer analytics platforms.
  • •Experience migrating EDW workloads (e.g., legacy SQL, Redshift, Snowflake, Synapse, EMR) across OLAP/OLTP systems, including query tuning, governance, and MPP debugging.
  • •Deep understanding of 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 of Python, Scala, or Java, with familiarity in telemetry/observability and security (SIEM tools such as Splunk, Elastic, Sentinel).
Experience:5+ years
Education:Bachelor's in Computer Science, Information Systems, Engineering
Skills:Technical leadershipMentorshipContinuous learningTechnical troubleshootingWorkload optimization
Languages:English
Tech Stack:Databricks Data Intelligence PlatformSpark StreamingKafkaSparkPythonScalaJavaSQLDelta LakeAWSAzureGCPRedshiftSnowflakeSynapseEMRSplunkElasticSentinelSIEM

Company Brief

Databricks
Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn