Data Engineer

About Avey

Position Overview

1. Data Pipeline Development & Maintenance

• Design, build, and operationalize complex ETL/ELT pipelines to process, clean, and normalize large volumes of structured and unstructured healthcare data (e.g., EHR/EMR, medical imaging, clinical notes, genomics).
• Develop and maintain data workflows and orchestration using tools like Apache Airflow, Prefect, or similar.
• Ensure the reliability, efficiency, and scalability of all data pipelines.
• Cost optimization (storage, compute, retention).

2. Analytics & Business Intelligence

• Design, develop, and maintain interactive and user-friendly analytics dashboards and reports for various business units using BI tools (e.g., Tableau, Power BI, Looker).
• Work with stakeholders to gather requirements and translate business questions into technical specifications for BI solutions and ad-hoc analyses.
• Present data-driven insights to both technical and non-technical audiences to support strategic decision-making.

3. Data Architecture & Modeling

• Architect and manage data storage solutions, including data lakes, data warehouses, and feature stores, on cloud platforms (AWS, Azure, or GCP).
• Develop data models and database schemas that are optimized for analytics, machine learning, and application performance.
• Implement best practices for data management and governance.

4. Data Quality & Compliance

• Implement rigorous processes for data quality assurance, data validation, and anomaly detection.
• Work closely with the security and compliance teams to ensure all data handling practices are compliant with healthcare regulations, including HIPAA and GDPR.
• Develop and enforce data anonymization and de-identification procedures to protect patient privacy.

5. Collaboration & Support

• Collaborate with data scientists to understand their data requirements and provide the necessary infrastructure and tools for model training and validation.
• Work with software engineers to integrate data services and APIs into our end-user products.

Requirements

• STEM degree or equivalent practical experience.
• Working experience in multi-cloud architecture & disaster recovery.
• Experience in API-based ingestion (rate limits, pagination, retries)
• LLM / AI data pipelines (dataset generation, batch inference, validation, OCR, multimodal data processing (text + images)
• Parallel processing & pipeline performance optimization
• Large-scale data ingestion (web scraping, multi-source pipelines with fallback)
• Dimensional modeling (Kimball) & Slowly Changing Dimensions (SCD)
• Delta Lake / Lakehouse architecture
• Nice to Have:
• Healthcare Experience (HIS/EMR systems, Cerner is a huge plus).
• Prior GCC Experience (NIA Qatar, HIPAA, or GDPR)
• Experience working in a Startup environment.
• Autoscaling inference APIs.
• CKA/CKAD/CKS or AWS/Azure certs.

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