Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🌲 North Carolina – Remote

🌲 North Carolina – Remote

💵 $115.5k - $173.3k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Teleflex

WebsiteLinkedInAll Job Openings

10,000+ employees

🏥 Healthcare

🏭 Manufacturing

⚕️ Healthcare Insurance

💰 $275k Venture Round on 2010-01

Healthcare • Manufacturing • Healthcare Insurance

Teleflex is a global provider of innovative medical devices and solutions, dedicated to supporting healthcare professionals and enhancing patient care. With a diverse portfolio that includes products for anesthesia, emergency medicine, interventional cardiology, and more, Teleflex aims to improve the health and quality of lives. The company emphasizes its commitment to education and customer support in the healthcare sector.

📋 Description

• Design, build, and maintain scalable, production-grade data pipelines for large-scale datasets • Develop and maintain ETL/ELT workflows across source systems, cloud platforms, and analytical environments • Monitor, troubleshoot, and optimize pipelines for availability, performance, and data integrity • Implement data quality checks, validation frameworks, and anomaly detection • Maintain technical documentation for pipelines, data models, and data dictionaries • Architect and manage Microsoft Azure data infrastructure • Provision, configure, and maintain cloud-based virtual machines and compute environments • Validate and monitor cloud-based storage for governance, security, and regulatory compliance • Design and manage data lakehouse and warehousing solutions • Implement workflow orchestration, scheduling, and dependency management • Apply database administration principles, including performance tuning, indexing, backup and recovery, and access management • Contribute to data governance through cataloging, lineage tracking, metadata management, and role-based access control • Improve pipeline efficiency, latency, and throughput • Apply data mining and profiling techniques to assess source data and data quality • Develop reusable data transformation components, libraries, and templates • Evaluate and adopt tools, frameworks, and cloud services • Operate distributed data processing workflows using Apache Spark and Databricks • Collaborate with data scientists and biostatisticians on analytical and machine learning workloads • Support HPC and large-scale batch processing • Interface with external data and analytics partners and vendors on data delivery, integration, APIs, and specifications • Manage and document data access agreements, ingestion schedules, and data refresh cadences

🎯 Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field • 5+ years of experience with a bachelor’s degree, or 3+ years with a master’s or PhD, in a data engineering role • Demonstrated expertise building and maintaining production-grade data pipelines • Strong ETL experience, including transforming data between models and data standardization • Strong proficiency in Python and SQL • Hands-on experience with Microsoft Azure data services, including Azure Data Factory, Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics or equivalent • Experience with ETL pipeline development and workflow orchestration tools such as Apache Airflow, dbt, or Azure Data Factory • Experience with distributed computing and big data frameworks such as Apache Spark or Databricks • Understanding of data modeling, data warehousing, and cloud storage formats such as Parquet and Delta Lake • Experience with Git, code review, and CI/CD • Strong written and verbal communication skills • Ability to collaborate with technical and non-technical stakeholders • Familiarity with provisioning and managing virtual machines and cloud compute resources is a plus • Master’s degree or PhD is preferred • Broader AWS and/or GCP experience is preferred • R programming experience is preferred • HPC and large-scale batch processing experience is preferred • Familiarity with Docker, Kubernetes, or Azure Kubernetes Service is preferred • Experience supporting data science and machine learning teams, MLOps, or model-serving infrastructure is preferred • Healthcare, medical device, pharmaceutical, or life sciences data experience is preferred • Familiarity with ICD, CPT4, LOINC, SNOMED CT, or OMOP CDM is a plus but not required • Strong organizational, communication, and documentation skills • Ability to make independent decisions and take responsibility for own actions • Ability to collaborate effectively and participate in a team environment • Excellent verbal and written communication skills

🏖️ Benefits

• Medical, prescription drug, dental, and vision insurance • Flexible spending accounts • Participation in 401(k) savings plan • Paid time off (PTO) • Short- and long-term disability benefits • Parental leave • Up to 10% expected travel