Junior Data Engineer - MedTech Lakehouse & Databricks

Hilo; Indiana (PA); Hybrid; USD 99,132 - 136,307; Full time

Benefits offered by this job

Remote-first

Hybrid setup

Competitive compensation

Job summary

Hilo by Aktiia is seeking a Junior Data Engineer to scale a Databricks-based medallion Lakehouse from R&D to a broader company-wide data platform. You’ll ingest, centralize, and document clinical and legacy data, turning messy sources into reliable, model-ready pipelines for Data Science and ML teams.

You’ll work with Python/SQL, Databricks, and AWS in a hybrid Swiss setup, collaborating with cross-functional stakeholders to ensure data quality and observability.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Engineering, Data Science, Software Engineering, or a related field.
• At least 1+ year of practical post‑study experience in data engineering, data infrastructure, data ingestion, or similar role.
• Solid hands‑on experience with Python and SQL and practical experience with Databricks; familiarity with AWS; basics of ETL/ELT pipeline design; data modelling; and Git/CI/CD practices.

Responsibilities

• Design, build, and maintain data ingestion and processing pipelines in Databricks medallion Lakehouse.
• Ingest, centralize, document clinical data from various sources (Castor, RedCap, databases).
• Work with unfamiliar data, identify structures/inconsistencies, and produce reliable data assets.
• Build preprocessing and ETL/ELT pipelines for model-ready datasets for ML and Data Science teams.
• Define data quality, validation, traceability, and documentation standards.

Skills

Python

SQL

Databricks

Cloud (AWS)

ETL/ELT

Data modeling

Git

CI/CD

Spark

Education

Bachelor's degree

Tools

Spark

Delta Lake

Parquet

Castor

RedCap

Job description

Hilo by Aktiia is seeking a Junior Data Engineer to scale a Databricks-based medallion Lakehouse from R&D to a broader company-wide data platform. You’ll ingest, centralize, and document clinical and legacy data, turning messy sources into reliable, model-ready pipelines for Data Science and ML teams.

You’ll work with Python/SQL, Databricks, and AWS in a hybrid Swiss setup, collaborating with cross-functional stakeholders to ensure data quality and observability.