Data Engineer – Apache Airflow, Spark, AWS

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Become part of a mission-oriented health technology organization that is establishing a global evidence network.

• Contribute to a core data engineering team tasked with the design and operation of data pipelines.

• Ingest, transform, and standardize real-world health data.

• Convert intricate source data frameworks into established healthcare data standards (FHIR, OMOP-CDM).

• Maintain data quality, security, and scalability throughout the platform.

• Thrive in a dynamic, engineering-focused environment.

⛳️ Requirements

• Proficient in advanced SQL — handling complex transformations, optimizing performance, and data modeling.

• Strong expertise in Python for developing and automating data pipelines.

• Demonstrated senior-level experience as a Data Engineer, with a history of scaling data products from pilot phases to production.

• Practical experience in constructing and enhancing big data pipelines, architectures, and datasets using tools like Apache Airflow and/or Apache Spark.

• Familiarity with AWS technologies (Redshift, S3, or similar managed services).

• Strong analytical capabilities when dealing with unstructured and semi-structured datasets.

• Solid grasp of data science principles and Big Data concepts.

• Excellent written and verbal communication skills in English (B2+ level).

• Self-motivated, with a strong sense of ownership and a proactive approach to problem-solving.

• NICE TO HAVE (Preferred): Experience with health data frameworks such as OMOP-CDM and/or FHIR.

• Knowledge of additional stack components such as Dagster, Trino, ClickHouse, and Airbyte.

• Experience in data quality assurance, including writing test specifications and test case scenarios.

• Background in healthcare or life sciences data environments.

• Experience working in agile/continuous delivery engineering teams.

🏝️ Benefits

• Fully remote position.