Data Engineer

About myTomorrows myTomorrows is a global health tech company dedicated to breaking down barriers for patients seeking treatment options. We strive to enable earlier and better treatment access by bridging the gap between those searching for possible options, and the companies who develop them. We work closely with patients, healthcare professionals, trial sites, patient advocacy groups, and BioPharma – connecting key stakeholders in the drug development ecosystem. We’ve developed a cutting-edge AI-powered technology platform that simplifies and streamlines access to drugs in development. To support our users and clients, we have a range of industry-expert specialized teams ready to help. Our services include clinical trial patient recruitment, Expanded Access Program management and Real-World Data collection. With a global footprint spanning 134 countries, to date we’ve supported over 17,000 patients, 3,000 physicians and 350 sites, earning the trust of 60+ BioPharma companies. In October 2025, we closed a €25M investment with Avego Healthcare Capital to fuel our global ambitions and scale the business. Join us in shaping the future of treatment access - making tomorrow’s therapies accessible for people who need them today. THE OPPORTUNITY As a Data Engineer at myTomorrows, you will play a key role in shaping the data infrastructure that powers our product platform and supports data-driven decision-making across the company. Working closely with our Data Analysts, DevOps team, and Product & Engineering colleagues, you will build a robust and scalable data environment that enables reliable data flow, storage, and visualisation. WHAT YOU’LL DO IN THIS ROLE: - Work within the Engineering and Product teams, closely collaborating with Marketing and Growth to develop reliable reporting pipelines - Design, build, and maintain robust data and reporting pipelines that deliver actionable insights to business stakeholders - Develop and evolve scalable, reliable data architectures for analytics and reporting use cases - Partner with business analysts and stakeholders to understand reporting needs and translate them into effective data solutions - Ensure compliance with industry standards and best practices for healthcare data management and data quality - Continuously improve data reliability, observability, and documentation - Stay up to date with emerging trends and technologies in data engineering and analytics WHAT YOU BRING TO THE TABLE: 1. Strong experience building and maintaining modern data pipelines using Python, DBT, and ETL tools such as Airflow 2. Hands-on experience loading and transforming data from multiple sources, including HubSpot, Google Analytics, relational databases (MySQL, PostgreSQL), NoSQL databases (e.g. DynamoDB), and various data formats 3. Experience working with data visualization tools such as Tableau 4. Solid understanding of data modeling, data architecture, and analytics best practices 5. Working knowledge of software development lifecycles and agile methodologies 6. Strong problem-solving skills and the ability to collaborate effectively within a small, cross-functional data team 7. Clear and confident communication skills in English What success looks like in 6 months After 6 months, the Data Engineer has developed a deep understanding of our data stack, domains, and business context, and is operating as a trusted technical partner across the organisation. They have audited and improved the existing data architecture, proactively identifying and addressing data quality gaps through automated validation and alerting. They independently design and own end-to-end data models, translating ambiguous business requirements into scalable, maintainable technical solutions. Stakeholders rely on them to shape data roadmaps, align data strategy with business goals, and make sound architectural decisions. The data platform is more reliable, performant, and cost-efficient as a result of their work, with pipelines m