Databricks에서 Specialist Solutions Architect를 채용합니다. 고객의 빅데이터 솔루션 구축을 지원하며, Apache Spark 및 데이터 기술에 대한 전문성을 바탕으로 아키텍처 설계와 성능 최적화를 수행합니다. 고객 대면 기술 역할 경험과 Python/Scala/Java 등 프로그래밍 역량이 필수입니다. 데이터 엔지니어링 또는 ML 분야의 깊은 전문성을 갖춘 분을 찾습니다.
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As a Specialist Solutions Architect (SSA), you will guide customers in building big data solutions on Databricks that span a large variety of use cases. These are customer-facing roles, working with and supporting the Solution Architects, requiring hands-on production experience with Apache Spark™ and expertise in other data technologies. SSAs help customers through design and successful implementation of essential workloads while aligning their technical roadmap for expanding the usage of the Databricks Lakehouse Platform. As a deep go-to-expert reporting to the Director of Field Engineering, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs and establish yourself in an area of specialty - whether that be performance tuning, machine learning, industry expertise, or more.
You will have experience in a customer-facing technical role with expertise in at least one of the following:
Software Engineer/Data Engineer: query tuning, performance tuning, troubleshooting, and debugging Spark or other big data solutions.
Data Scientist/ML Engineer: model selection, model lifecycle, hyper parameter tuning, model serving, deep learning.
Data Applications Engineer: Build use cases that use data - such as risk modelling, fraud detection, customer life-time value.
Experience with design and implementation of big data technologies such as Spark/Delta, Hadoop, NoSQL, MPP, OLTP, and OLAP.
Maintain and extend production data systems to evolve with complex needs.
Production programming experience in Python, R, Scala or Java
Deep Specialty Expertise in at least one of the following areas:
Experience scaling big data workloads that are performant and cost-effective.
Experience with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration, REST API, BI tools and SQL Interfaces.
Experience designing data solutions on cloud infrastructure and services, such as AWS, Azure, or GCP using best practices in cloud security and networking.
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.
Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
Native level Korean is required and Business level English is a plus
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
**Benefits
**At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
