Sr. Solutions Engineer - Digital Native Business, FinTech (FinTech)

TL;DR

Sr. Solutions Engineer - Digital Native Business, FinTech (FinTech): Designing and implementing big data architectures for sophisticated data engineering and science teams with an accent on Spark, Delta Lake, and MLflow. Focus on building proof-of-concepts for strategic projects and integrating cloud services to solve complex business problems.

Location: Remote (US); candidates in other locations will be considered. Must be available to travel to customers in the region.

Salary: $152,300 — $209,450 USD

Company

Databricks is a data and AI company providing a Data Intelligence Platform to unify data, analytics, and AI for over 10,000 organizations worldwide.

What you will do

• Partner with sales teams to provide technical leadership and help customers solve business problems.
• Consult on Big Data architectures and implement proof of concepts for data engineering, data science, machine learning, and SQL analysis workflows.
• Validate integrations with cloud services, proprietary tools, and 3rd party applications.
• Promote and recruit contributors for Databricks-inspired open-source projects including Spark, Delta Lake, and MLflow.

Requirements

• 3+ years of experience in data engineering, data science, technical architecture, or a similar pre-sales/consulting role.
• Proven experience building distributed data systems.
• Proficiency in programming and debugging with Python and SQL.
• Experience building solutions with public cloud providers such as AWS, Azure, or GCP.
• Expertise in Data Engineering (Spark, Hadoop, Kafka) or Data Science/ML (pandas, scikit-learn, pytorch, Tensorflow).
• Availability to travel to customers in the region.

Nice to have

• Degree in a quantitative discipline such as Computer Science, Applied Mathematics, or Operations Research.
• Databricks Certification.

Culture & Benefits

• Comprehensive benefits and perks tailored to the specific employee region.
• Commitment to fostering a diverse and inclusive culture with equal employment opportunity standards.
• Opportunity to work with some of the most sophisticated data engineering and science teams in the world.