Specialist Solutions Architect - Data Engineering

Amsterdam · 5+ years experience · Hybrid · Posted Oct 14, 2026

At a glance

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.

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.

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.
Design, build, and optimize scalable, high-performance batch and streaming pipelines, operational data layers (Lakebase), and end-to-end performance load testing on Databricks.
Build and operationalize custom user-facing data applications using Databricks Apps, transforming data pipelines and AI models into interactive tools.
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.
Mentor peers, contribute reusable architecture assets, and deliver technical workshops and community presentations to scale expertise across accounts and field teams.

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).
Demonstrated daily reliance on AI coding tools and LLMs to accelerate pipeline development, troubleshooting, and asset generation.
Strong production coding skills in Python, SQL, and Scala or Java, with a solid grasp of data modeling and system design fundamentals.
5+ years in pre-sales or post-sales technical consulting, managing customer engagements and navigating multi-stakeholder technical discussions.
Practical experience with operational/transactional data layers (Postgres/OLTP), low-latency serving, reverse ETL, and hybrid transactional/analytical processing.

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