Data Engineer

Accountabilities:

• • Design, build, and maintain scalable and reliable data pipelines using Python, PySpark, and SQL.
  • Develop, optimize, and maintain ETL and data transformation processes to deliver accurate and relevant information for internal reporting and products.
  • Collaborate with Product Managers, Designers, Leadership, and Engineering teams to understand requirements and translate them into effective data solutions.
  • Build scalable, well-structured, and discoverable data models using SQL, supported by clear and comprehensive documentation.
  • Implement data quality checks, monitoring, and validation processes to maintain data accuracy, consistency, and integrity.
  • Optimize data storage and retrieval processes for performance, scalability, and cost efficiency.
  • Contribute to the optimization and maintenance of data-processing clusters and ensure efficient resource utilization.
  • Establish and promote data engineering best practices across processing, modeling, documentation, and development workflows.
  • Document technical processes, data models, and engineering practices clearly for internal stakeholders and, where appropriate, client-facing audiences.
  • Continuously improve team workflows, engineering processes, and development practices.
  • Take ownership of individual objectives and contribute to broader team and business goals through measurable outcomes.
  • Proactively investigate data challenges, conduct research, make informed technical decisions, and drive solutions independently.

  Requirements:

  • 2–4 years of professional experience in a Data Engineering role, ideally involving internal, financial, or operational reporting.
  • Strong proficiency in Python, including dataframes, object-oriented programming, modularity, and maintainable code practices.
  • Practical experience with PySpark and large-scale data processing.
  • Strong SQL skills, including the ability to write complex queries, data transformations, and data quality checks.
  • Proven experience with data modeling and query optimization.
  • Experience building or maintaining scalable data infrastructure in a growing SaaS or technology environment is highly desirable.
  • Experience with Databricks and dbt is a strong advantage.
  • Familiarity with databases such as ClickHouse is a plus.
  • Understanding of DevOps principles and CI/CD practices is advantageous.
  • AI fluency and familiarity with emerging AI development concepts such as MCP, agents, and cross-agent review is a plus.
  • Strong analytical and problem-solving abilities, with creativity, independent thinking, and a proactive approach to technical challenges.
  • Ability to take ownership, conduct independent research, and make sound conclusions in an evolving environment.
  • Strong collaboration and communication skills, with the ability to work effectively with engineers, product teams, designers, leadership, and other stakeholders.
  • Strong organizational and time-management skills, including the ability to prioritize work independently and manage tight deadlines.
  • Comfortable working under pressure while maintaining high standards of quality.
  • Full professional proficiency in English, both written and spoken.

  Benefits:

  • Fully remote working environment across Europe.
  • Competitive compensation and benefits.
  • Opportunity to work in a meaningful healthcare-related technology sector.
  • Chance to contribute to products supporting professionals and improving digital patient care.
  • Learning and professional development opportunities.
  • Access to the tools and technologies needed to perform your work effectively.
  • Autonomy and ownership within a continuously improving engineering environment.
  • Opportunity to work with talented colleagues across multiple countries and cultures.
  • International, collaborative, and fast-growing SaaS environment.
  • Exposure to modern data engineering, AI-assisted development, large-scale data processing, and cloud technologies.
  • Company events and opportunities to connect with colleagues around the world.
  • Meaningful opportunity to influence data infrastructure, quality, scalability, and engineering practices as the organization continues to grow.