Specialist Solutions Architect

Databricks Databricks · Data AI · Seoul, South Korea · Field Engineering - Other

This role is for a Specialist Solutions Architect at Databricks, focusing on guiding customers in building big data and AI solutions on the Databricks Lakehouse Platform. The role involves architectural design, data engineering, and model deployment, with a strong emphasis on production-level workloads, performance tuning, and optimization. Experience with Apache Spark, MLflow, and cloud platforms is crucial, as is the ability to provide technical leadership in customer-facing engagements.

What you'd actually do

  1. Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
  2. Architect production level workloads, including end-to-end pipeline load performance testing and optimisation
  3. Provide technical expertise in an area such as data management, cloud platforms, data science, machine learning, or architecture
  4. Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing, and custom architectures
  5. Improve community adoption (through tutorials, training, hackathons, conference presentations)

Skills

Required

  • customer-facing technical role
  • Apache Spark/Delta
  • Python, R, Scala or Java
  • ML concepts covering Model Tracking, Model Serving
  • productionizing ML pipelines
  • Databricks Lakehouse Platform
  • AWS, Azure, or GCP
  • Native level Korean

Nice to have

  • expertise in other data technologies
  • performance tuning
  • machine learning
  • industry expertise
  • Hadoop, NoSQL, MPP, OLTP, and OLAP
  • Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration, REST API, BI tools and SQL Interfaces
  • cloud security and networking
  • Business level English

What the JD emphasized

  • customer-facing
  • production experience
  • technical leadership
  • architectural design
  • data engineering
  • model deployment
  • performance tuning
  • machine learning
  • production programming
  • production data systems
  • productionizing ML pipelines

Other signals

  • customer-facing
  • big data solutions
  • Databricks Lakehouse Platform
  • architectural design
  • data engineering
  • model deployment
  • pipeline performance testing
  • MLflow
  • productionizing ML pipelines