Partner Solutions Architect

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

Partner Solutions Architect at Databricks, focusing on enabling partners to leverage the Databricks Data Intelligence Platform for data-driven outcomes. Responsibilities include technical enablement, workshops, architecture design, and solution development using technologies like Apache Spark, MLflow, and Delta Lake.

What you'd actually do

  1. Provide partners with the level of enablement they need to assist their clients in evaluating and adopting Databricks including hands-on Apache Spark™ programming and integration with the wider cloud ecosystem
  2. Engage with the partner technical community by leading workshops, seminars, and meet-ups
  3. You will be a Big Data Analytics expert on aspects of architecture and design and will share this with our partner network
  4. Show expertise by producing creative technical solutions and blog post

Skills

Required

  • 5+ years of pre-sales or post-sales experience working with external clients or partners
  • Understanding of customer-facing pre-sales or consulting role
  • Experience demonstrating technical concepts, including presenting and whiteboarding
  • Experience developing architectures within a public cloud (AWS, Azure, or GCP)
  • Coding experience in SQL, Python, Scala, or Java
  • Expertise in Data Engineering technologies (Ex: Apache Spark™, Hadoop, Kafka)
  • Expertise in Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
  • Expertise in Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO)
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience
  • Native-level fluency in Korean
  • Professional working proficiency in English

Nice to have

  • MLflow
  • Delta Lake

What the JD emphasized

  • core strength in either data engineering or data science
  • Expertise in at least one of the following: Data Engineering technologies (Ex: Apache Spark™, Hadoop, Kafka) / Data Warehousing (Ex: SQL, OLTP/OLAP/DSS) / Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO)