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. #J-18808-Ljbffr