Solutions Architect (Data Engineering)

TL;DR

Solutions Architect (Data Engineering): Designing and implementing complex big data architectures and machine learning workflows for high-growth digital native businesses with an accent on platform integration and technical leadership. Focus on building scalable data engineering pipelines, validating cloud-native solutions, and driving technical adoption of the Databricks Data Intelligence Platform.

Location: Remote (USA). Preference for candidates in Nevada, California, Colorado, Oregon, or Washington, but open to other US locations.

Salary: $180,000 – $247,500 USD

Company

Databricks is the data and AI company, creators of the Lakehouse architecture, Apache Spark, Delta Lake, and MLflow, serving over 10,000 organizations worldwide.

What you will do

• Partner with sales teams to provide technical leadership and solve complex business problems for customers.
• Consult on big data architectures and implement proof-of-concepts for data engineering, data science, and SQL workflows.
• Validate integrations with cloud services, internal tools, and third-party applications.
• Collaborate with fellow Solutions Architects to support users and share technical expertise.
• Promote and recruit contributors for Databricks-inspired open-source projects within the developer community.

Requirements

• 5+ years of experience in data engineering, data science, technical architecture, or pre-sales consulting.
• Proven experience building distributed data systems.
• Proficiency in Python and SQL for programming and debugging.
• Hands-on experience 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).
• Ability to travel to customer sites within the assigned region.

Nice to have

• Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research).
• Databricks Certification.

Culture & Benefits

• Comprehensive benefits and perks tailored to regional needs.
• Commitment to diversity, inclusion, and equal employment opportunity.
• Opportunity to work with cutting-edge data and AI technologies at a global scale.
• Collaborative environment focused on professional growth and technical excellence.