Junior Data Engineer

📋 Description

• • Build and maintain production data pipelines using dbt models, Airflow DAGs, Airbyte connectors, and BigQuery transformations, ensuring reliability and scalability from day one.
• • Contribute directly to integrations between AMBOSS’s data platform and core business systems such as ERP, developing and maintaining code for internal tools like the global master data management service for medical institutions.
• • Collaborate with Data Analysts and Data Scientists to enable self-serve analytics, ensuring the platform meets their needs through close partnership and shared ownership of data quality.
• • Use AI tools like Claude Code to enhance productivity while developing the judgment to critically evaluate outputs and determine when to trust or discard them.
• • Work side-by-side with senior engineers through pair programming, code reviews, and feedback loops to accelerate technical growth and deepen understanding of the production stack.
• • Engage in stakeholder conversations to understand the business context behind data requests, ensuring solutions align with real-world needs before implementation begins.
• • Uphold high standards of quality by writing tests, documenting code, implementing observability, and treating small details as critical components of the job—not someone else’s responsibility.
• • Stay tool-agnostic by evaluating new technologies based on evidence and business impact, not trend or novelty, while remaining open to evolving tooling as the platform grows.
• • Approach problems by first understanding the ‘why’ behind a task, prioritizing business context over premature code optimization, and asking ‘what is this for?’ before deciding how to build it.
• • Think systemically by connecting technical changes to broader pipelines, schemas, and business workflows, avoiding narrow solutions that create downstream issues.
• • Thrive in ambiguity by learning quickly across new tools, domains, and layers of the stack without waiting for perfect briefs, preferring to experiment and iterate rather than delay action.
• • Challenge assumptions—including your own—by sanity-checking code, flagging uncertainty, and ensuring all outputs are grounded in verified facts rather than speculation.
• • Build with the next maintainer in mind, investing in clean foundations, readable code, and thorough documentation to reduce future overhead and enable sustainable growth.
• • Work openly with colleagues, asking for help early when stuck, providing direct feedback, and valuing collaborative problem-solving over solitary effort.
• • Participate in cross-functional meetings with Product, Engineering, Commercial, Medical, and Operations teams to align data work with organizational goals and user impact.
• • Ship production-grade code and data solutions within your first weeks, contributing meaningfully to platforms used by medical professionals worldwide to support clinical decision-making.
• • Maintain curiosity about emerging technologies such as vector databases, CI/CD pipelines, Infrastructure as Code, and ERP integrations, even if not yet experienced.
• • Apply SQL fundamentals including joins, window functions, and CTEs to transform and model data effectively within BigQuery.
• • Leverage Python skills to build small data tools or scripts end-to-end, automating repetitive tasks and supporting pipeline development.
• • Gain exposure to cloud environments (GCP or AWS) and modern data stack tools including dbt, Airflow, and Airbyte in a live, high-impact production setting.
• • Develop an instinct for balancing speed and quality, prioritizing long-term maintainability over short-term shortcuts to ensure sustainable engineering practices.
• • Understand and respect the unique mission of AMBOSS: empowering medical professionals with data-driven tools that improve patient care across 180+ countries.