FEQ427R349
As a Sr. Solutions Architect, you are an expert-level technical leader responsible for the organisation's most complex customer engagements. You drive consumption strategy, own executive-level relationships, and serve as the definitive technical authority for your accounts. You have declared your archetype—a recognised technical specialisation that makes you a force multiplier across your team and region. You operate at the intersection of deep technical expertise, strategic account planning, and executive influence.
The Impact You Will Have
- Drive the technical and consumption strategy for the organization's most complex customer engagements, directly influencing platform adoption and revenue growth.
- Own senior-level technical relationships — serving as a trusted advisor on enterprise data and AI strategy
- Lead the most complex architecture engagements: multi-workload platforms, enterprise-wide migrations, real-time systems, and AI/ML at scale
- Operate as an Expert on the Databricks Platform with a declared archetype — actively mentoring others and driving horizontal impact across your team
- Develop and execute competitive strategies for your customers, positioning Databricks against incumbent and emerging platforms
- Orchestrate cross-functional teams (DSAs, SSAs, Partners, Product) to deliver enterprise-grade solutions
- Coach and develop junior SAs (L3–L5) on technical depth, customer engagement, and use case prioritization
- Contribute to Field Engineering thought leadership through customer-facing content, workshops, and community engagement
What We Look For
- 8+ years in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role
- Expert-level coding proficiency — Python, SQL, and ideally Spark/PySpark. You will complete a live coding assessment and a platform build during the interview
- Deep expertise in enterprise data architecture: distributed systems at scale, streaming/real-time, lakehouse design patterns, data governance frameworks, and cloud-native platforms
- Expert-level Databricks Platform knowledge (or equivalent depth in competing platforms with demonstrated rapid learning ability)
- Declared technical specialization with recognized depth — e.g., real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions
- Proven track record of driving consumption growth and platform adoption in large accounts
- Executive presence — ability to influence Directors, VPs, and C-level stakeholders on long-term data and AI strategy
- Experience leading competitive displacements and complex enterprise evaluations
- Strong strategic thinking — connecting technical architecture decisions to business outcomes and revenue impact
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience); advanced degrees are valued
- Ability to travel on a weekly basis
Nice to Have:
- Full professional proficiency in English and German
- Financial Service expertise with executive-level domain credibility
- Databricks certifications
- Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company
- Published thought leadership (blogs, conference talks, open source contributions)
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
- 8+ years of experience in solutions architecture, principal engineering, technical pre-sales leadership, or senior customer-facing technical roles
- Expert-level coding proficiency in Python and SQL; ideally Apache Spark or PySpark
- Deep expertise in enterprise data architecture, distributed systems, streaming, lakehouse design, data governance, and cloud-native platforms
- Expert-level knowledge of the Databricks Platform or equivalent expertise in competing platforms with demonstrated ability to learn rapidly
- Recognized technical specialization in areas such as real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions
- Proven record of driving consumption growth and platform adoption in large enterprise accounts
- Executive presence and ability to influence Directors, VPs, and C-level stakeholders
- Experience leading competitive displacements and complex enterprise evaluations
- Strong strategic thinking connecting technical architecture decisions to business outcomes and revenue impact
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience
- Ability to travel on a weekly basis
- Full professional proficiency in English and German
- Financial services expertise with executive-level domain credibility
- Databricks certifications
- Experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data and AI company
- Published thought leadership, conference talks, blogs, or open-source contributions
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.
