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At Marktplaats, data is at the heart of everything we do, but Intelligence is what differentiates us. We are building the Data Platform that powers innovation across our entire Product & Technology landscape.

You will join the Data Platform team—the engineering backbone of the Data & Analytics crew. We are a group of passionate engineers building the ecosystem that powers innovation across Marktplaats. Rather than just maintaining pipelines, we are architecting a high-scale environment where backend services meet analytical insights. You will be stepping into a collaborative culture that values autonomy and solving complex distributed systems problems, acting as a pivotal player in our evolution.

As a Senior Staff Data Engineer - Data Platform, you will be relied upon to design the architecture and lead the implementation of our Databricks-based Data Platform. Your mandate is to ensure reliability, scalability, and cost-effectiveness while driving a true self-serve vision. You will build the "Golden Paths," tooling, and Infrastructure-as-Code automation that empower users to work independently with minimal blockers.

You will act as the architectural bridge between Platform Engineering, Product, and Data teams. You will collaborate on the full lifecycle of analytic data, defining Data Contracts and Quality Standards to ensure seamless flow and consumption across the organization. You are a Strategic Modernizer who looks beyond the status quo, constantly evaluating new paradigms and introducing them where they add tangible business value.

• Platform Leadership: Lead the evolution of our Data Platform and architect the "Data Exchange" strategy. You will define robust patterns for API-based ingestion, Event-Driven Architectures (Kafka), and Reverse ETL to connect Product teams with the Platform, while ensuring architectures are optimized for cost and performance on AWS.

• Continuous Modernization: Act as a catalyst for technical evolution. You constantly scan the horizon for next-generation technologies, evaluating them not just for novelty, but for their ability to simplify our architecture and improve developer experience. You lead the implementation of new paradigms that tangibly lift our engineering standards and make our platform more efficient.

• Governance & FinOps: Design the strategy for Unity Catalog implementation and Data Contracts, ensuring robust governance, lineage, and Data Quality standards. You also champion FinOps, automating cost controls for our highest-volume workloads.

• Enablement: Build the underlying infrastructure that allows Analytics/DWH teams to run efficient transformations (using dbt, Star Schema, Medallion Architecture) without bottlenecks.

• Mentorship: Elevate the technical bar of the team, mentoring Staff and Senior engineers on distributed systems concepts, backend design patterns, and code quality.

• Translation: Translate complex architectural trade-offs into clear strategies for Product Managers and Backend Leads, ensuring alignment on data generation standards.

• Databricks Data Stack: Unity Catalog, Delta Lake, Delta Live Tables, Databricks Workflows, Photon Engine.

• Big Data & Compute: Apache Spark (Internals & Optimization), AWS (Networking, Compute, Security).

• Ingestion & Streaming: Kafka (and similar Event Buses), Flink, Spark Streaming.

• Orchestration & Transformation: Airflow, dbt.

• Languages: Python (Expert level), Scala (Strong proficiency for backend integration).

• Infrastructure as Code: Terraform, Terragrunt.

• Containerization: Docker, Kubernetes.

• CI/CD: GitHub Actions.

• Observability: Datadog.

• Experience:10+ years of hands-on experience in Software Development or Data Engineering, with at least 5+ years specifically focused on building Data Platforms, with a deep understanding of how Platform infra supports Analytics workloads.

• Architectural Evolution: Proven experience evolving complex platforms. You have a track record of moving from legacy patterns to modern, cloud-native solutions (e.g., monolithic ETL to modular Lakehouse).

• Spark Mastery: You don't just run jobs; you optimize them. You possess deep knowledge of Spark internals, JVM tuning, and performance optimization for high-scale batch and streaming datasets.

• Databricks Lakehouse Mastery: Deep expertise in Unity Catalog, Delta Lake internals, and optimizing high-volume workloads.

• Backend Roots: You have the heart of a Backend Engineer but the mind of a Data Architect. You apply strict software engineering discipline (CI/CD, Testing, OOP) to data pipelines and understand microservices architecture.

• Analytics Synergy: You understand the needs of Analytics/DWH teams (Data Modeling, dbt) and ensure the platform supports them efficiently.

• DevOps Mindset: You treat infrastructure as software. You have a strong background in building automated pipelines using Terraform/Terragrunt and ensuring system observability.

• Collaborative Spirit: You speak the language of Backend Engineers and Data/Product people, effectively bridging the gap between "Application Data" and "Analytical Data".