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Lead Data Platform Engineer

  • Hybrid
    • Amsterdam

Job description

Build the foundation of data-driven transformation 

At Riverflex, we design and deliver scalable digital solutions that empower companies to harness the full value of data. We’re looking for a Lead Data Platform Engineer to join our internal team—bringing deep technical expertise and leadership to build, scale, and evolve our data infrastructure. 

In this role, you’ll architect cloud-native data platforms, lead the development of data pipelines and tooling, and guide a team of engineers in building robust, secure, and real-time data systems. You’ll work cross-functionally with product, analytics, and client delivery teams—driving best-in-class data engineering practices and enabling data products that fuel transformation. 


The Role 

You’ll take technical ownership of Riverflex’s data engineering stack, leading hands-on development while setting standards and mentoring others. You’ll play a key role in designing scalable systems that unlock insights and power intelligent products. 


Responsibilities 

  • Architect and maintain end-to-end data platforms across cloud environments (Azure, Databricks) 

  • Design and implement secure, scalable, and automated data pipelines. 

  • Collaborate with analytics, product, and engineering teams to translate business needs into data solutions 

  • Own data platform reliability, performance, monitoring, and incident response 

  • Implement and champion best practices in data modelling, governance, testing, and documentation 

  • Mentor junior engineers and help shape a high-performing data engineering team 

  • Evaluate and integrate new technologies to improve data stack performance, scalability, and cost-efficiency 

  • Build reusable tooling, components, and internal frameworks for data pipeline development 

  • Ensure compliance with data privacy, protection, and security regulations (e.g. GDPR) 


Job Requirements 

Must-Haves 

  • 6+ years of experience in data engineering or data infrastructure roles 

  • Strong proficiency in Python, SQL, and distributed data frameworks (e.g., Spark, Kafka, Airflow) 

  • Proven experience building data platforms in a cloud-native environment (Azure preferred) 

  • Deep understanding of data lakehouse architectures and modern data warehousing (e.g., Databricks) 

  • Hands-on experience with DevOps practices for data (CI/CD, IaC, Terraform, Docker) 

  • Strong understanding of data governance, privacy, and compliance frameworks 

  • Comfortable working in fast-paced, cross-functional Agile teams 

  • Excellent communication and stakeholder management skills 


Nice-to-Haves 

  • Experience leading technical teams or mentoring data engineers 

  • Exposure to MLOps and enabling data pipelines for ML use cases 

  • Familiarity with real-time data processing and event-driven architectures 

  • Experience with dbt, Looker, or other modern data stack tools 

  • Previous consulting or client-facing experience 


What We Offer 

  • 25 days off per year plus closure between Christmas and New Year's. 

  • Flexible remote work from abroad options for up to 6 weeks per year. 

  • Learning & Development budget, including full access to Udemy courses. 

  • Classpass membership to support well-being. 

  • Latest tech & tools, including home office budget and professional software subscriptions. 

  • Equity share scheme to give long-term team members ownership in Riverflex. 

  • Annual company trips to celebrate successes together. 

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