Solutions Architect Greenfield Enterprise France

Posted 8 Days Ago
Be an Early Applicant
Paris, Île-de-France, FRA
In-Office
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Lead technical strategy for new enterprise customers, design scalable data and AI architectures, guide Databricks adoption, conduct architecture discussions, build custom solutions, coordinate cross-functional resources, and advise senior technical stakeholders. The role requires strong Python and SQL skills, distributed data systems expertise, public cloud deployment experience, and fluency in French and English.
Summary Generated by Built In

FEQ128R5

Solutions Architect Greenfield Enterprise France

The role is based in Paris or within commuting distance of the office.

The Role

As a Solutions Architect, you will lead the technical strategy for your Greenfield (New Logo) customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain.

The Impact You Will Have

  • Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth
  • Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics
  • Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
  • Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions
  • Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain
  • Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs
  • Influence product direction by providing structured feedback on customer requirements and competitive gaps

What We Look For

  • 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
  • Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
  • Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
  • Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
  • Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis
  • Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
  • Track record of driving platform adoption and consumption growth within accounts
  • Excellent communication skills — able to translate complex architectures into business value for both technical and executive audiences
  • Fluency in French and English
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:

  • Databricks certifications (Data Engineer, ML, Platform)
  • Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
  • Background in a data/AI company or cloud provider
  • Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.

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

  • 6+ years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
  • Strong coding proficiency in Python and SQL, including live coding, debugging, and solution building
  • Deep expertise in distributed data systems architecture, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
  • Proficiency with the Databricks Platform or demonstrated ability to achieve proficiency rapidly
  • Experience leading architecture discussions with senior technical stakeholders, including whiteboarding, design reviews, and trade-off analysis
  • Experience with production deployments on AWS, Azure, or GCP, including infrastructure, security, and governance
  • Track record of driving platform adoption and consumption growth within accounts
  • Excellent communication skills for translating complex architectures into business value
  • Fluency in French and English
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience
  • Databricks certifications in Data Engineering, ML, or Platform
  • Experience with Snowflake, AWS native services, or Azure Synapse
  • Background in a data/AI company or cloud provider
  • Industry domain expertise in Financial Services, Healthcare, Retail, Media, or similar sectors

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.

  • Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision for employees and dependents, plus dedicated mental-health resources and an EAP. Wellness and gym reimbursements further support wellbeing.
  • Equity Value & Accessibility — Equity grants (RSUs/stock options) are highlighted as a major part of compensation and are often viewed as attractive. Occasional tender-offer liquidity and performance bonuses reinforce total rewards.
  • Parental & Family Support — Paid parental leave, fertility benefits, and subsidized backup dependent care are emphasized. Family medical leave and caregiver support also feature in the package.

Databricks Insights

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The Company
HQ: San Francisco, CA
2,200 Employees
Year Founded: 2013

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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