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 RoleYou’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)
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
- 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.