Data Engineer

• Ontwerpen, opzetten en doorontwikkelen van ETL- en ELT-processen binnen Microsoft Fabric.
• Ontsluiten en integreren van data uit bronsystemen zoals Topicus (EPD), AFAS (ERP) en de Waarneemapp via API’s en databasekoppelingen.
• Inrichten van een gestructureerde dataomgeving met een heldere scheiding tussen ruwe data en gemodelleerde datasets.
• Ontwikkelen van datamodellen (o.a. sterschema’s) die geschikt zijn voor analyse en rapportage in Power BI.
• Ontwikkelen van dashboards en rapportages die management ondersteunen bij operationele, tactische en strategische sturing.
• Bewaken en verbeteren van datakwaliteit, consistentie en beveiliging binnen het dataplatform.
• Optimaliseren van performance, schaalbaarheid en kosten binnen de cloudomgeving.
• Meedenken over de verdere inrichting en architectuur van het dataplatform binnen Microsoft Fabric.
• Verkennen en toepassen van advanced analytics, zoals predictive modellen en AI, waar dit waarde toevoegt.
• Samenwerken met verschillende afdelingen en bijdragen aan adoptie van Power BI en datagedreven werken.

Senior Data Engineer

• Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies.
• Lead system-wide architectural decisions, focusing on data flow, performance, and resilience.
• Actively contribute to the codebase with high quality code.
• Lead major technical initiatives, reduce technical debt and ensure the platform meets the reliability and scalability SLAs.
• Collaborate with product and engineering teams and R&D management to define the technical roadmap, review architecture and mentor junior engineers

Principal Data Engineer

• As a Data Engineer, you will spend your time helping clients achieve their data engineering needs.
• You’ll also make a real impact by taking an active role in the team’s Agile Development practices, technical decision making and development, generating value and continuously striving to improve the quality and reliability of our data and processes.
• You will spend the majority of your time helping deliver client data engineering opportunities and supporting the growth of our junior-mid level technologists; both within AND and for our clients.
• Stack Migration: Migrating the existing data processing stack (PostgreSQL/Jenkins/Python) to a modern cloud-based stack (AWS/Airflow/Redshift/Python/PySpark/Spark), ensuring continuity and data integrity throughout the transition.
• Design and Build Scalable ETL Pipelines: Build and optimise ETL/ELT data pipelines, focusing on performance, scalability, and data integrity.
• Maintain and Develop Data Pipelines: Support and maintain existing pipelines while building new ones to meet evolving business needs and stakeholder requirements.
• Streaming & Integration: Develop and maintain both batch and real-time data processing pipelines from multiple data sources.
• Support DevOps Practices: Contribute to CI/CD processes for testing, building, and deploying data pipelines.
• Performance Optimisation: Tune pipeline performance for both batch and real-time data processing.
• Collaboration and Mentorship: Partner with internal teams and engineers to ensure seamless data integration.

Data Engineer – Contract

• Lead the design and implementation of enterprise data governance strategies and frameworks;
• Partner with data owners, data stewards, and senior stakeholders to align governance with business objectives;
• Define and enforce data governance standards to ensure data quality, integrity, and security;
• Oversee data governance activities, including data quality management, cataloging, and metadata initiatives;
• Drive training and awareness programs to embed governance practices across the organization;
• Monitor compliance, manage risks, and resolve complex data governance issues;
• Establish governance metrics and reporting to track effectiveness and maturity;
• Stay current on industry best practices and continuously improve governance processes.

Senior Data Architect

• Lead data engineering teams to new heights and foster an environment for growth.
• Guide engineers in enabling a modern, secure, and scalable data infrastructure.
• Cultivate a positive and supportive team culture by establishing healthy rituals.
• Coach and mentor team members to support their individual growth and career advancement.
• Establish the team as a Center of Excellence by driving best practices and knowledge sharing.
• Own the full talent lifecycle, from hiring to performance management.
• Collaborate with Product Owners, Architects & Tech Leads to ensure team well-being and performance.

People Manager, Data Engineering

• Step into a role as a Data Engineer with one of our clients through the CFGdegree programme
• These job roles are linked directly to free education
• Upon completion of our course, you will be equipped to start your role as a Junior Data Engineer

Junior Data Engineer

• Bouwen van concrete oplossingen binnen onze dataregisters
• Ontwikkelen en onderhouden van webservices (REST API's met Pydantic/FastAPI), gehost als Azure Function Apps
• Beheren en optimaliseren van databases in SQL Server met SQLAlchemy, inclusief het schrijven en tunen van stored procedures
• Inrichten en beheren van Managed Identities voor veilige authenticatie tussen services en de database
• Testen van API's en endpoints met Bruno om kwaliteit en stabiliteit te borgen
• Meebouwen aan het DKS (DataKwaliteitsSysteem) om de kwaliteit van onze data structureel te borgen en verbeteren
• Opzetten en onderhouden van CI/CD pipelines in Azure DevOps voor geautomatiseerde en betrouwbare deployments
• Monitoren van applicaties en services met Application Insights, inclusief het opzetten van logging en alerting om issues snel te signaleren
• Werken in een Agile omgeving en schakelen met verschillende stakeholders binnen de organisatie
• Meedenken over technische keuzes en de doorontwikkeling van ons dataplatform in Azure

• Design, build, and operate scalable data infrastructure on AWS
• Develop and maintain batch and streaming pipelines using Databricks and Spark
• Improve reliability, scalability, performance, and resilience of data systems
• Support modern lakehouse architecture and enterprise analytics use cases
• Design and maintain Bronze, Silver, and Gold data layers following Medallion Architecture
• Build trusted datasets for reporting, analytics, and self-service consumption
• Improve data quality, lineage, consistency, and governance standards
• Support reusable and scalable data models across business domains
• Build, maintain, and evolve infrastructure using Terraform
• Design reusable, well-structured Terraform modules for shared data platform capabilities
• Improve standards for versioning, testing, documentation, and lifecycle management
• Collaborate with teams to safely provision resources through IaC workflows
• Support and manage two environments across development and production
• Improve deployment automation and release consistency between environments
• Ensure stable promotion paths for pipelines, infrastructure, and platform changes
• Contribute to CI/CD standards and DevOps best practices
• Implement secure access controls, IAM roles, and least privilege principles
• Support monitoring, alerting, logging, and operational excellence across the platform
• Contribute to data governance, privacy, and compliance initiatives
• Troubleshoot incidents and continuously improve reliability
• Monitor and optimize AWS and Databricks platform spend
• Improve workload efficiency, cluster utilization, and resource management
• Partner with teams to design cost-conscious data solutions

• Analyze user behavior, product performance, and key business metrics to identify trends and opportunities.
• Create and maintain interactive dashboards and reports using tools like Tableau, Looker, Power BI, or Google Data Studio.
• Collect, clean, and structure large datasets to ensure accuracy and usability.
• Define and track KPIs for marketing, product, and business performance.
• Work with SQL, Python, or R to extract, analyze, and manipulate data.
• Collaborate with product managers, engineers, and marketing teams to provide data-driven insights.
• Conduct A/B testing and experiment analysis to improve product features and user engagement.
• Identify bottlenecks and opportunities in user journeys and customer funnels.
• Present findings in a clear and compelling way to stakeholders and leadership teams.
• Stay up to date with industry trends, analytics best practices, and emerging data tools.

• Wil jij als Data Engineer Financiële Informatievoorziening in Den Haag bouwen aan een nieuw rijksbreed dataplatform?
• Bij het FDC ontwikkel je datastromen en zorg je voor betrouwbare financiële data die ertoe doet.
• Als data engineer werk je aan de ontwikkeling van een nieuw rijksbreed informatielandschap.
• De eerste twee jaar ben je gedetacheerd bij de systeemeigenaar.
• Daar ben je vanaf de start betrokken bij het ontwerpen en opbouwen van de dataomgeving en help je bij het neerzetten van een toekomstbestendig dataplatform.
• Na deze periode ga je aan de slag bij het Financieel Dienstencentrum (FDC).
• Met jouw kennis zorg je voor het beheer en de verdere ontwikkeling van de dataomgeving.
• Je draagt bij aan een stabiele, betrouwbare en goed ingerichte informatievoorziening die aansluit op de behoeften van de organisatie.
• In je dagelijkse werk bouw en optimaliseer je datastromen en datamodellen.
• Je ontwikkelt datamarts vanuit verschillende databronnen en verbetert ETL-processen.
• Daarbij bewaak je datakwaliteit en performance.
• Je werkt nauw samen met BI-specialisten en stakeholders en zorgt dat datastromen en technische keuzes helder zijn vastgelegd.

Senior Data Engineer – Financiën

• Design and implement a modern, scalable data architecture for HR and people analytics
• Build and maintain data pipelines (ETL/ELT) to integrate data from systems like Workday and other sources
• Ensure accurate, consistent, and reliable data integration across all platforms
• Structure and optimize the data lake according to best practices
• Translate security and compliance requirements into robust data engineering solutions
• Implement data lifecycle management processes, including retention and purging
• Ensure data quality through monitoring, testing, and validation (e.g. dashboards and reporting)
• Collaborate closely with technical teams and stakeholders
• Document data architecture, processes, and security standards
• Support auditability, traceability, and backup/recovery strategies

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