Solutions Architect

Summary

Join Databricks as a Specialist Solutions Architect (SSA) and guide customers in building big data solutions on the Databricks platform. This customer-facing role requires hands-on experience with Apache Spark and other big data technologies, particularly in the Data Science domain. You will provide technical leadership, scale customer data science workloads, and build ML pipelines. The position involves supporting customers, improving community adoption, and assisting Solutions Architects in the technical sales process. You will contribute to the Databricks community as a technical SME. This remote-friendly role requires significant experience in machine learning, cloud infrastructure, and big data technologies.

Requirements

• Pre-sales or post-sales experience working with external clients across a variety of industry markets
• Experience in a technical role involving the design, implementation, and operationalisation of Machine Learning models in production
• Hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch
• Experience building production-grade machine learning solutions on AWS, Azure, or GCP
• Experience building Machine Learning solutions on cloud infrastructure and services, such as AWS, Azure, or GCP leveraging a strong understanding of: Model development including building, training, tuning, and evaluation processes
• Different types of ML algorithms and methods, including supervised and unsupervised machine learning, and Deep Learning methods
• MLOps concepts covering model monitoring, tracking, management, model serving & deployment, and other aspects of productionising ML pipelines in distributed data processing environments using tools like MLflow
• Ability to design highly performant, scalable, and cost-effective cloud-based data & ML solutions, such as distributed training and inference processes on GPU clusters
• Experience with big data technologies such as Spark/Delta, Hadoop, NoSQL, MPP, and OLAP
• Deep knowledge in development tools and best practices for engineers including CI/CD, unit and integration testing, and automation and orchestration
• Proven ability to maintain and extending production data systems to evolve with complex needs
• Strong programming experience in Python and potentially R
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience

Responsibilities

• Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to model deployment and operations
• Scale customer data science workloads, architecting new production level workloads, including end-to-end machine learning pipelines
• Build, scale and optimize customer data science workloads and apply best-in-class MLOps to productionize these workloads across a variety of domains
• Support our customers solve critical data problems by leveraging your technical SME skills
• Improve community adoption by providing tutorials and training, including hackathons and conference presentations
• Assist Solutions Architects with in-depth aspects of the technical sales process, such as advanced custom proof of concepts, sizing complex workloads, and designing custom architectures
• Contribute to the Databricks Community and act as a technical SME

Preferred Qualifications

This role can be remote, but we prefer that you are located in the job listing area and can travel up to 30% when needed

Benefits

For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks