Data Engineer

Our client, an esteemed healthcare organization dedicated to transforming supply chain operations, is hiring a Data Engineer. This role offers an exciting opportunity for a skilled Data Engineer to design, build, and maintain scalable data pipelines and analytical models supporting enterprise supply chain analytics and operations. The position involves working with large-scale healthcare data environments, ensuring data quality, and enabling advanced analytics initiatives within a collaborative and innovative department. The ideal candidate will play a vital role in supporting data integration, reporting, operational decision-making, and transformation efforts, contributing to advancements in healthcare supply chain management.

Responsibilities

• Build and maintain scalable, efficient data pipelines and transformation workflows aligned with business requirements.
• Develop and refine analytical and dimensional data models for enterprise use.
• Integrate data from diverse enterprise sources, including healthcare and supply chain systems.
• Implement comprehensive data quality measures, validation, and troubleshooting procedures to ensure data integrity.
• Optimize data processing performance and storage efficiency considering enterprise standards.
• Support production workflows through troubleshooting, issue resolution, and continuous monitoring.
• Maintain detailed documentation, including metadata and data lineage, adhering to data governance policies.
• Collaborate closely with technical and business teams to gather requirements and develop innovative data solutions.

Requirements

• Minimum of 3 years of experience as a Data Engineer, particularly in building and maintaining production data pipelines.
• Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field.
• Strong proficiency in Python, SQL, and data pipeline development techniques.
• Hands-on experience with ETL/ELT processes, data modeling, and data quality assurance.
• Expertise with Databricks, Apache Spark, and PySpark is preferred; experience with cloud-based data engineering platforms is essential.
• Knowledge of data validation, troubleshooting, and production support environments.
• Experience working in healthcare data systems such as Epic, Oracle, GHX, ParEx, or PeopleSoft is advantageous but not mandatory.
• Familiarity with BI tools like Tableau and Alteryx, and exposure to forecasting or machine learning initiatives is a plus.
• Ability to work in a hybrid environment, with at least 2 days onsite (Wednesdays & Thursdays).
• Strong communication skills and the ability to partner with cross-functional teams.
• Additional desirable qualifications include experience supporting healthcare supply chain analytics, familiarity with data governance, and experience mentoring junior team members. Candidates from diverse industries with a robust data engineering background are encouraged to apply.

Some of the Benefits

• Competitive salary.
• Hybrid work model with flexible scheduling.
• Opportunity to work with large-scale healthcare datasets and enterprise systems.
• Collaborative work environment fostering professional growth and innovation.
• Access to cutting-edge cloud-based data engineering tools and platforms.

Salary: The posted range is not a guarantee. The actual salary will be based on qualifications, experience, and education and could fall outside of this range. Contact us for more information.
#LI-NI1