.png)
(FEQ128R2)
As a Specialist Solutions Architect (SSA) – Data Engineering, you are a hands-on technical authority who guides strategic customers in designing, building, and optimizing production-grade data workloads on the Databricks Data Intelligence Platform. Partnering closely with Account Teams and Solution Architects, you translate complex big data challenges into high-performance, scalable architectures using Apache Spark™ and modern streaming frameworks.
In this role, you will drive successful implementations, align technical roadmaps to accelerate platform adoption, and establish deep domain specialization; whether in real-time streaming, performance optimization, or operational data layers, while expanding your impact across Field Engineering.
- Drive Technical Wins & Scope: Lead end-to-end technical design, proof of concepts (PoCs), and workload sizing for strategic customer engagements, acting as a trusted advisor to front-line technical stakeholders to secure technical wins.
- Architect Production Data Systems: Design, build, and optimize scalable, high-performance batch and streaming pipelines, operational data layers (Lakebase), and end-to-end performance load testing on Databricks.
- Deploy Interactive Data Applications: Build and operationalize custom user-facing data applications using Databricks Apps, transforming data pipelines and AI models into interactive tools.
- AI-Native Engineering: Leverage AI coding assistants, LLMs, and agentic workflows (e.g., Genie Code, Cursor) as a force multiplier to rapidly prototype, debug, and deliver architectural assets with full ownership of outputs.
- Enablement & Domain Leadership: Mentor peers, contribute reusable architecture assets, and deliver technical workshops and community presentations to scale expertise across accounts and field teams.
- Deep Data Engineering Expertise: 5+ years in data or software engineering with hands-on proficiency in distributed processing (Apache Spark™, Delta Lake, SDP) and real-time streaming technologies (Spark Streaming, Kafka, CDC).
- AI-First Builder Mindset: Demonstrated daily reliance on AI coding tools and LLMs to accelerate pipeline development, troubleshooting, and asset generation.
- Production Programming & Foundations: Strong production coding skills in Python, SQL, and Scala or Java, with a solid grasp of data modeling and system design fundamentals.
- Customer Advisory & Delivery: 5+ years in pre-sales or post-sales technical consulting, managing customer engagements and navigating multi-stakeholder technical discussions.
- Operational & HTAP Architectures: Practical experience with operational/transactional data layers (Postgres/OLTP), low-latency serving, reverse ETL, and hybrid transactional/analytical processing.
- Cloud & Migration Mastery: Hands-on experience with major cloud platforms (AWS, Azure, GCP) and legacy data lake modernisation (e.g., Hadoop migration and cost optimisation).
- Application Experience: Background in constructing specialised data applications (e.g., risk modelling, fraud detection, customer lifetime value) across industries as a data expert.
- Ecosystem & Culture Contribution: Active track record of technical community engagement, public speaking, open-source contributions, or peer mentoring and interviewing.
- Flexibility & Travel: Ability to travel up to 30% for strategic customer engagements and internal alignment.
- This will be an office-based contract (Amsterdam), with a hybrid schedule, requiring up to 30% travel when needed for customer visits, events & trainings.
- An initial 12-month fixed-term contract is to be offered, with the expectation of extending/converting to FTE upon successful completion of the probation period.
#LI-hybrid
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
- 5+ years of experience in data engineering or software engineering
- Hands-on experience with distributed processing technologies including Apache Spark, Delta Lake, and Spark Declarative Pipelines
- Experience with real-time streaming technologies such as Spark Streaming, Kafka, and change data capture
- Daily use of AI coding tools and large language models to accelerate development and troubleshooting
- Strong production programming skills in Python, SQL, and Scala or Java
- Knowledge of data modeling and system design fundamentals
- 5+ years of pre-sales or post-sales technical consulting experience
- Experience managing customer engagements and multi-stakeholder technical discussions
- Practical experience with operational or transactional data layers, PostgreSQL or OLTP, low-latency serving, reverse ETL, and HTAP architectures
- Hands-on experience with AWS, Azure, or GCP
- Experience with Hadoop migration and data lake modernization
- Experience building specialized data applications such as risk modeling, fraud detection, or customer lifetime value solutions
- Technical community engagement, public speaking, open-source contributions, peer mentoring, or interviewing experience
- Ability to travel up to 30%
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 — 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.
-
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.
-
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.
