Job description
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.
