Data Engineer - Healthcare

At Statista
, we’re all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions.

Founded in Hamburg in 2007, we have quickly grown into a global company with offices in major cities such as London, New York, Berlin and Tokyo. And we still have a lot of plans. Our constant growth does not only prove our success, but also keeps creating new development and career opportunities for our employees.

We value and celebrate our diverse culture. You are welcome here for who you are, no matter where you come from, what you look like, or whether you prefer bar graphs to pie charts. Your story matters – keep writing it as part of our team.

Are you ready to join us?

Statista Healthcare is a vertical business unit of Statista, focused on making healthcare quality transparent, measurable, and comparable across countries, care settings, and specialties. We work with leading healthcare stakeholders worldwide to support data-driven quality measurement and transformation by combining in-depth analytical expertise with scalable technology and communication power.

Our offerings span international rankings, ratings, benchmarking studies, and customized consulting projects. Our global healthcare rankings and hospital ratings are published in collaboration with our trusted media partner Newsweek, enabling high visibility and credibility across markets.

We help healthcare organizations define relevant key performance indicators, validate and harmonize data structures, and translate insights into actionable strategies. At the heart of our approach is a data driven understanding of healthcare quality, grounded in robust methodologies, global comparability, and stakeholder trust.

In our consulting projects, we support healthcare providers and systems in developing tailored KPI frameworks, standardizing and validating data processes, and deriving actionable insights that enable measurable improvements in patient care and system-level performance. We combine structured methodologies with hands-on delivery to unlock the full value of healthcare quality data.

As the Data Engineer on our Healthcare Platform, you’ll own data ingestion and platform reliability end-to-end: designing and operating scalable batch/streaming pipelines, hardening orchestration, ensure data quality, security, and cost efficiency. You’ll partner closely with our Analytics Engineer (who leads data modeling) to deliver clean, well-governed datasets, and with Data Scientists and Data Analysts to make high-quality healthcare data accessible and trustworthy for analysis and products.

• Develop and optimize ELTs to integrate new data sources and enhance data management in the data warehouse (DWH) and other systems
• Drive cross-functional collaboration with engineering, data science, and analysis teams to deliver documented, reproducible datasets for healthcare KPIs, benchmarking, and product features
• Drive business outcomes through data solutions (e.g., reducing cost, increasing accessibility)

• Data Ingestion / ELTs and Orchestration:
  Ability to fetch and prepare data using Python and SQL. Familiarity with a data orchestration tools like Prefect, Airflow, etc. Familiarity with data ingestion from Files, S3, Iceberg tables, APIs, databases and external sources.
• Cloud Platform Expertise:
  Hands‑on experience with Amazon Web Services (AWS), including services like Snowflake, S3, EC2 and ECS. Knowledge of best practices for data storage, security and scalability on AWS. Power
  
  BI and DBT is a plus.
• CI/CD and Automation (Github Actions):
  Implementation of CI/CD pipelines for seamless software development and deployment. Automation of data workflows, reducing manual effort and ensuring efficiency.
• Infrastructure as Code (IaC):
  Proficiency in using Terraform to define and provision cloud infrastructure (AWS resources). Ability to create and manage infrastructure declaratively, ensuring version control and reproducibility.