Senior Solutions Engineer - Big Data Architect & ML

Databricks; York (York County); On-site; USD 152,000 - 209,000; Full time

Job summary

Databricks is seeking a Sr. Solutions Engineer on the Digital Natives team to shape the future of the big data landscape by collaborating with leading data engineers and data scientists.

You will guide customers through architectures, implement proofs of concepts, and promote platform capabilities across cloud ecosystems. You will partner with sales, support data engineering and ML workflows, and drive open-source initiatives like Spark, Delta Lake, and MLflow while traveling to customer sites

Qualifications

• 3+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role.
• Experience building distributed data systems.
• Comfortable programming in Python and SQL.
• Have built solutions with AWS, Azure, or GCP.
• Expertise in data engineering and data science tech (Spark, Hadoop, Kafka) or ML libs.
• Willing to travel to customers in your region.
• Desired degree in quantitative discipline; Databricks Certification is a plus.

Responsibilities

• Partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Consult on big data architectures, implement proofs of concepts for strategic projects, spanning data engineering, data science and ML workflows.
• Collaborate with fellow Solutions Architects to support users.
• Become an expert in, promote, and recruit contributors for Databricks open-source projects (Spark, Delta Lake, MLflow).

Skills

Python

SQL

Data engineering

Data science

Pre-sales

Cloud platforms

Education

Degree in quantitative discipline

Tools

Spark

Hadoop

Kafka

pandas

scikit-learn

pytorch

Tensorflow

AWS

Azure

GCP

Job description

Databricks is seeking a Sr. Solutions Engineer on the Digital Natives team to shape the future of the big data landscape by collaborating with leading data engineers and data scientists.

You will guide customers through architectures, implement proofs of concepts, and promote platform capabilities across cloud ecosystems. You will partner with sales, support data engineering and ML workflows, and drive open-source initiatives like Spark, Delta Lake, and MLflow while traveling to customer sites