The Role
As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage.
The Impact You Will Have
- Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
- Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins
- Own frontline technical relationships with customer engineers, data teams, and technical leads
- Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption
- Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations
- Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community
What We Look For
- 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
- Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage
- Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
- Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
- Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
- Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics
- Strong presentation and demo skills — you will build and present a live solution during the interview
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
Nice to Have:
- Databricks certification or experience with the Databricks Platform
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
- Background at a data/AI company, cloud provider, or technical consulting firm
Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- 4+ years of experience in data engineering, solutions architecture, technical pre-sales, or hands-on consulting
- Proficiency in Python and SQL, including debugging, optimization, and production-quality coding
- Hands-on experience designing and implementing data solutions on AWS, Azure, or GCP
- Working knowledge of distributed data systems such as Apache Spark, Delta Lake, Hadoop, Kafka, or Flink
- Experience leading technical customer conversations, including discovery, whiteboarding, and architecture reviews
- Familiarity with data engineering, data science and machine learning, or SQL analytics
- Strong presentation and live demonstration skills
- Bachelor's or Master's degree in Computer Science, Engineering, quantitative discipline, or equivalent experience
- Databricks certification or Databricks Platform experience
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
- Background at a data or AI company, cloud provider, or technical consulting firm
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
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Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
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Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
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