Resident Solutions Architect

Mission

At Databricks we work on some of the most complex distributed processing and machine learning problems in the world and our customers continually challenge us with interesting new big data and AI use cases. As a Resident Solutions Architect at Databricks, you will have the opportunity to shape the future big data and the machine learning landscape for leading Fortune 500 organizations.  

This position is a senior level, customer-facing role that requires deep hands-on expertise in Apache Spark and Machine Learning, along with a breadth of knowledge of the big data ecosystem. On a weekly basis, you will strategically guide our largest customers, lead their architecture design, and implement pipelines from data engineering through model building and deployment. A successful Resident Solutions Architect is curious, self-motivated, and excels in cross-functional collaboration. As part of joining Databricks, you will have a direct channel to the developers of Apache Spark, Delta Lake, and MLflow, and the opportunity to attend and present at top big data conferences.  

Outcomes

• Guide strategic customers as they design and implement big data and machine learning projects, ranging from business transformational projects, through to end-to-end machine learning model build and deployment
• Leverage your deep expertise in building machine learning products to guide customers to do the same, through building proofs of concept and prototypes, architecting solutions and even pair-programming with customer teams as necessary
• Architect, implement, and/or validate migration of workloads from 3rd party databases and data platforms to Apache Spark
• Evangelize Spark and Databricks, Delta Lake and MLflow across the developer community through meetups and conferences
• Plan and coordinate with Account Executives, Customer Success Engineers and Solution Architects for expanding the use of Databricks platform within strategic enterprise customers on a weekly basis

Competencies

• Design and implementation experience in Big Data technologies (Spark, Hadoop ecosystem, Kafka, NoSQL databases) and familiarity with data architecture patterns (data warehouse, data lake, streaming, Lambda/Kappa architecture)
• Familiarity with the full range of the machine learning space, both the mathematical and statistical theory and the technical applications of these methods
• Experience with building and deploying a range of machine learning models into production, including supervised and unsupervised machine learning and deep learning methods
• Experience with performance tuning, troubleshooting, and debugging Spark and/or other big data solutions
• Comfortable with talking up and down the IT chain of command including directors, managers, architects and developers
• Expertise programming in Python or Scala 
• Experience with cloud providers such as AWS, Azure or GCP
• Willing to travel 30-40% regionally
  

   

Benefits

• Competitive salary
• Medical Insurance
• Pension Plan
• Gym reimbursement
• Employee referral bonus program

About Databricks

Databricks’ mission is to accelerate innovation for its customers by unifying Data Science, Engineering and Business. Founded by the original creators of Apache Spark™, Databricks provides a Unified Analytics Platform for data science teams to collaborate with data engineering and lines of business to build data products. Users achieve faster time-to-value with Databricks by creating analytic workflows that go from ETL and interactive exploration to production. The company also makes it easier for its users to focus on their data by providing a fully managed, scalable, and secure cloud infrastructure that reduces operational complexity and total cost of ownership. Databricks, venture-backed by Andreessen Horowitz, NEA and Battery Ventures, among others, has a global customer base that includes Viacom, Shell, and HP.  For more information, visit www.databricks.com.

Apache, Apache Spark and Spark are trademarks of the Apache Software Foundation.