Report this job

---

What is the problem? *

Incorrect company
Incorrect location
Job is expired
Job may be a scam
Other

Responsible to lead the adoption of Apache Spark, Delta, Redash and Databricks and guide strategic customers as they design and implement big data projects ranging from architectural design to data engineering to machine learning model deployment. Detailed job duties include: Understanding customer requirements and evaluating various Databricks runtime spark technologies to fulfill them. Create initial proof of concept for building end-to-end solutions which satisfy customer requirements using Databricks spark technology platform. Designing overall end-to-end architecture. Development and review of the software modules. Provide best practices during implementations by creating working notebook templates in the Databricks platform. Provide technical guidance during the implementation phase of customers requirements. Develop programs using programming paradigms including: Scala, Python, SQL, Java, AWs cloud, Azure Cloud, Hadoop ecosystem components , RDMS , functional and Object Oriented programming , CI/CD. Develop meaningful test cases for the data pipeline being developed for customers. Assist the professional services leaders and project managers with level of effort estimation and mitigation of risk within customer proposals and statements of work. Build detailed troubleshooting guides and run books to enhance the efficiency of the customer. Develop tutorials and training for customers for new and complex distributed programming products that Databricks offer. Contribute to automation and tooling projects to make daily troubleshooting and efficient. $215,197 - $230,000 per year. Minimum job requirements: Master’s degree in Computer Science, Computer Engineering, Mathematics, Business Analytics or a related field and at least three years of experience. Will accept Bachelor’s degree plus five years of experience in lieu of Master’s degree plus three years of experience. Must have experience in the following areas: Experience with Apache Spark; Design and implementation experience in at least one of the following big data technologies: Hadoop, NoSQL, MPP, OLTP, or OLAP; experience working with at least one of the following fields: 1) software engineering/data engineering field including query tuning, performance tuning, troubleshooting and debugging Spark, or 2) data scientist/ML engineering field including model selection, model lifecycle, hyperparameter tuning, model serving, and deep learning; Programming experience with at least one of the following: Python, Scala or Java. May telecommute from any US location.