Data Engineer

1.     About AposHealth

AposHealth is an international healthcare company that has developed a clinician-led, non-invasive treatment program for musculoskeletal conditions. The Apos approach combines a personalized, foot-worn biomechanical device with ongoing clinical monitoring to redistribute joint loading, retrain gait, reduce pain, and improve function during daily activities.

Our mission is to improve quality of life by providing innovative, personalized, non-invasive solutions that reduce pain, restore function, and transform the management of musculoskeletal conditions.

2.     Role overview

We are seeking a passionate and hands-on Data Engineer to join our Analytics & Data Platform team. In this role, you will design, build, and optimize our central data platform, enabling AposHealth to operate as a truly data-driven organization. You will play a critical role in ingesting, transforming, and operationalizing large-scale healthcare and operational datasets, translating them into actionable insights that support decision-making, product innovation, and business growth.

3.     Data Platform Environment

You will work on AposHealth’s modern cloud-based data platform, which includes:

·      Orchestration: Dagster (self-hosted)

·      Infrastructure: AWS (EC2, S3, Athena, ECR, Secrets Manager)

·      Data Warehouse: PostgreSQL, Snowflake

·      Processing stack: Python (pandas, polars, DuckDB), SQLAlchemy, awswrangler

·      CI/CD: GitHub Actions

·      Data quality & monitoring: Automated asset checks and alerting

A self-hosted Dagster orchestration layer on AWS (Docker on EC2, ECR, S3, Secrets Manager) that ingests data from multiple information systems into a PostgreSQL data warehouse, with S3/Athena and Snowflake used for staging and HER data. The platform transforms that data into core business domains and pushes curated data back into some of the operating systems as well as extensive reporting mechanisms. Built in Python 3.11, the stack uses pandas/polars, SQLAlchemy, awswrangler, and DuckDB for processing, with GitHub Actions CI/CD, asset checks for data quality, and automated failure alerting.

4.     Key Responsibilities

4.1. Data Engineering & Architecture

• Design, build, and maintain scalable data pipelines (ETL/ELT)
• Expand and optimize the company’s Data Lake and Data Warehouse
• Integrate new internal and external data sources to enrich analytics capabilities

4.2. Platform Ownership

• Own and evolve the central orchestration platform (Dagster), including assets, jobs, schedules, sensors, and data quality checks
• Ensure system reliability, performance, and scalability

4.3. Data Quality & Governance

• Develop and implement data validation, monitoring, and alerting mechanisms
• Ensure data integrity, consistency, and platform health

4.4. Business Collaboration

• Work closely with business stakeholders, product, and analytics teams to:
• Translate business needs into data requirements
• Design and deliver end-to-end data solutions
• Contribute to the definition of KPIs, dashboards, and analytics products

4.5. Operational Excellence

• Maintain and improve data workflows, processes, and documentation
• Support production issues across the BI and data stack
• Drive continuous improvement of data infrastructure and practices

5.     Qualification & Experience

5.1. Required

·      3+ years of experience as a Data Engineer or in a similar role

·      Strong proficiency in SQL and Python (3+ years hands-on experience)

·      Experience with data orchestration tools (Dagster, Airflow, Prefect, etc.)

·      Solid experience with ETL/ELT pipelines, data modeling, and data integration

·      Experience working with AWS cloud services (e.g., S3, EC2, Athena, SQS)

·      Experience with Docker and containerized environments

·      Experience building and maintaining CI/CD pipelines (e.g., GitHub Actions)

5.2. Preferred

·      Experience with Dagster (strong advantage)

·      Familiarity with Snowflake and modern data stack tools

·      Experience with BI tools (e.g., Tableau)

·      Understanding of healthcare or clinical data environments

·      BSc in Computer Science, Information Systems, Engineering, or equivalent practical experience.

5.3. Key Competencies

·      Strong analytical and problem-solving skills

·      Ability to translate business needs into scalable technical solutions

·      Self-starter with full ownership mindset (end-to-end delivery)

·      Excellent communication and collaboration skills

·      High attention to detail and commitment to data quality

Please send your application to: [email protected]