Data Engineer

Overview

Our client, a leading healthcare organization focused on revolutionizing supply chain operations, is seeking a proficient Data Engineer. This role involves designing, constructing, and managing scalable data pipelines and analytical models that underpin enterprise-wide supply chain analytics and operational initiatives. The successful candidate will handle large healthcare datasets, ensure high data quality, and support advanced analytics efforts within a dynamic, innovative team.

Key Responsibilities

• Architect and sustain efficient, scalable data pipelines and transformation workflows based on business needs.
• Create and enhance dimensional and analytical data models for organization-wide usage.
• Aggregate and harmonize data from multiple enterprise systems, including healthcare and supply chain platforms.
• Deploy comprehensive data quality controls, validation methods, and troubleshoot data issues to preserve data accuracy.
• Optimize data processing speeds and storage utilization following enterprise best practices.
• Provide production support by monitoring workflows, resolving issues, and ensuring smooth operations.
• Maintain extensive documentation, including metadata details and data lineage, complying with governance policies.
• Partner with technical and business stakeholders to understand requirements and deliver innovative data-driven solutions.

Qualifications and Skills

• At least 3 years of experience in data engineering, focusing on production pipeline development and maintenance.
• Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related discipline.
• Strong command of Python and SQL combined with expertise in data pipeline development.
• Practical experience with ETL/ELT methodologies, data modeling, and quality assurance practices.
• Preferred knowledge in Databricks, Apache Spark, and PySpark; essential experience with cloud data engineering platforms.
• Skilled in data validation, troubleshooting, and supporting production environments.
• Experience with healthcare data systems such as Epic, Oracle, GHX, ParEx, or PeopleSoft is a plus, but not mandatory.
• Familiarity with BI software like Tableau and Alteryx, and exposure to forecasting or machine learning initiatives is advantageous.
• Ability to operate in a hybrid format with at least two days onsite (Wednesdays and Thursdays).
• Excellent communication skills and capacity to collaborate across multiple departments.
• Bonus qualifications include knowledge of healthcare supply chain analytics support, data governance practices, and mentoring junior staff. Applicants from varied industries with strong data engineering backgrounds are welcome.

Benefits

• Competitive remuneration package.
• Flexible hybrid working schedule.
• Exposure to large-scale healthcare datasets and enterprise-grade systems.
• A collaborative environment promoting growth and innovative thinking.
• Access to leading cloud-based data engineering technologies and platforms.

Additional Information

The salary listed is not a guarantee and will depend on individual qualifications, experience, and education; it may also fall outside the indicated range.