# Specialist Solutions Architect - Data Engineering at Databricks > Netherlands · Staff · Data engineering · open. Source: https://alderhq.app/jobs/greenhouse%3Adatabricks%3A8870159002 (read 2026-11-05). ## Facts (observed) - Company: [Databricks](https://alderhq.app/companies/databricks) - Location text: Amsterdam, Netherlands; Amsterdam, Netherlands - Where it can be done from (inferred): Netherlands (evidence: "Location: Amsterdam, Netherlands; Amsterdam, Netherlands") - Posted: 2026-10-14 (22 days ago) - First seen by alder: 2026-11-03 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://databricks.com/company/careers/open-positions/job?gh_jid=8870159002 - Skills listed (inferred): Python, Java, Scala, PostgreSQL, Kafka, AWS, GCP, Azure, Spark, SQL, LLMs, Distributed systems ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Amsterdam, n 3): p25 €73k, median €86k, p75 €92k - H-1B filings at this company for similar roles, FY26: 356, median offered wage $157k ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance)) - Recognised sponsor (NL): registered as "Databricks" (checked 2026-11-03, [register](https://ind.nl/en/public-register-recognised-sponsors/public-register-regular-labour-and-highly-skilled-migrants)) - Licensed UK sponsor: registered as "Databricks UK Limited" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) ## Description (the employer's text) (FEQ128R2) ### The Role 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. ### The impact you will have - 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. ### What we look for - 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. ### Nice to haves - 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. ### Notes on the role - 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Adatabricks%3A8870159002 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.