Data Engineer

2 days ago

Taguig, National Capital Region, Philippines St. Luke's Medical Center Full time
Overview

Data Engineer will focus on designing and managing scalable ETL/ELT pipelines to support real-time and batch processing of healthcare data across structured and unstructured formats. They will ensure compliance with data governance policies, enable interoperability between healthcare systems, and enforce strong data quality controls. Collaboration with data architects and custodians is key to maintaining secure, cost-efficient infrastructure and ensuring that all processes are well-documented and continuously monitored for performance and reliability.

Responsibilities
  • Design, build, and manage scalable ETL/ELT pipelines to support both real-time and batch processing of healthcare data for ingestion and transformation.
  • Ensure that pipelines can efficiently handle structured, semi-structured, and unstructured data from various healthcare systems such as EHRs, LIS, and PACS.
  • Implement end-to-end data processing workflows that include cleansing, enrichment, validation, and ensure alignment with data governance standards.
  • Make sure all pipelines comply with established data governance protocols, especially concerning data security, privacy, and regulatory compliance.
  • Automate data validation procedures and establish Data Quality KPIs to verify adherence to Key Data Elements (KDE) requirements.
  • Facilitate seamless integration of data across different systems and platforms while maintaining interoperability and consistency.
  • Work closely with Data Architects and Custodians to identify and resolve data quality issues through scalable and efficient solutions.
  • Optimize cloud-based data infrastructure for performance, scalability, and cost-effectiveness, ensuring systems are built for long-term use.
  • Continuously monitor pipeline performance, identifying and addressing issues such as failures, bottlenecks, or security risks proactively.
  • Collaborate with governance teams to ensure implemented solutions uphold data quality and governance standards.
  • Maintain comprehensive documentation of all data workflows, transformation logic, and pipeline processes to support transparency, maintenance, and issue resolution.
  • Performs other tasks and duties as may be assigned/delegated by the superiors.
Qualifications
  • Bachelor's degree in Computer Science/ Information Technology/ Computer Engineering or related fields
  • 1-3 years of experience.
  • Expertise in cloud-native data processing tools and frameworks (e.g., Apache Beam, Apache Spark, Dataflow, Dataproc).
  • Proficiency in SQL, Python, and Java for data transformation and pipeline development.
  • Hands-on experience with orchestration tools (e.g., Apache Airflow, Cloud Composer).
  • Keep understanding of CI/CD pipelines and infrastructure-as-code (e.g., Terraform, CloudFormation).
  • Experience implementing automated data quality checks using tools like Great Expectations or custom validation frameworks.
  • Proficiency in using monitoring tools (e.g., Stack driver, CloudWatch, Grafana) to ensure pipeline reliability.
  • Experience managing PHI/PII securely in cloud environments.

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