Lead Data Platform Engineer

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.

Build the foundation of data-driven 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