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Resident Solutions Architect 1161 views

As a Resident Solutions Architect, you will have the opportunity to shape the future big data landscape for leading Fortune 500 organizations. This position is a senior-level customer-facing role that requires deep expertise in Apache Spark™ along with a breadth of big data solution architecture experience.

On a weekly basis, you will guide customers through architecture, design, and implementation while strategically aligning their technical roadmap for expanding the usage of the Databricks platform. As part of the RSA team, you will continue to strengthen your technical expertise through mentorship, continuous learning, and internal training programs. This role can be remote, but the ideal candidate will be located in the job listing area and have a willingness to travel up to 30%.


    • Provide technical leadership in a post-sales capacity to guide strategic customers as they design and implement big data projects, ranging from architectural design to data engineering to model deployment
    • Identify and drive new initiatives that enable customers to turn their data into actionable business value and align these initiatives with their business outcomes for continued success
    • Architect production-level workloads, including an end to end pipeline load performance testing and optimization
    • Deliver tutorials and training to drive community adoption (including hackathons, conference presentations, etc.)
    • Work closely with Engineering and Product Management to drive the direction of the Databricks product
    • Contribute to Databricks SME community


  • Hands-on and superior technical experience with Apache Spark
  • Proven experience of design and implementation experience in big data technologies including Hadoop, NoSQL, MPP, OLTP, OLAP
  • 5+ years of experience working as either:
  • Software Engineer/Data Engineer: query tuning, performance tuning, troubleshooting, and debugging Spark and/or other big data solutions.
  • Data Scientist/ML Engineer: model selection, model lifecycle, hyperparameter tuning, model serving, deep learning, etc.


  • Comfortable programming in Python, Scala or Java
  • Experience using and designing solutions on cloud infrastructure and services, such as AWS, Azure, or GCP
  • Experience with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration, REST API, BI tools, and SQL Interfaces. E.g. Jenkins
  • Proven experience with ML concepts covering Model Tracking, Model Serving and other aspects of productionizing ML pipelines in distributed data processing environments like Apache Spark, using tools like MLflow
  • Excellent communication skills and comfortable presenting to strategic stakeholders/leadership
  • Experience in customer-facing pre-sales, post-sales, technical architecture guidance, or consulting
  • Passionate about learning new technologies and making customers successful



    • Comprehensive health coverage including medical, dental, and vision
    • 401(k) Plan
    • Equity awards
    • Flexible time off
    • Paid parental leave
    • Family Planning
    • Gym reimbursement
    • Annual personal development fund
    • Employee Assistance Program (EAP)

About Databricks

Databricks is the data and AI company. Founded by the original creators of Apache Spark™, Delta Lake, and MLflow, Databricks simplifies data and AI so data teams can collaborate and innovate faster. More than five thousand organizations worldwide —including Shell, Conde Nast, and Regeneron — rely on Databricks as a unified platform for massive-scale data engineering, collaborative data science, full-lifecycle machine learning, and business analytics. Venture-backed and headquartered in San Francisco (with offices around the globe) Databricks is on a mission to help data teams solve the world’s toughest problems. To learn more, follow Databricks on Twitter, LinkedIn, and Facebook.

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