Specialist Solutions Architect - Data Engineering
(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.
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