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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer (Remote) - **Company:** Teleflex - **Location:** Morrisville, NC, United States (Remote available) - **Experience:** Experienced - **Salary:** $115,500.0 - $173,300.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Microsoft Azure, Backup Devices, Batch Processing, Big Data, Clinical Data Repository, Cloud Computing, Cloud Database, Cloud Storage, Code Review, Information Systems, Continuous Integration, Data as a Services, Data Auditing, Data Validation, Data Dictionary, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Extract Transform Load (ETL), Data Transformation, Data Mining, Data Security, Data Systems, Data Warehousing, Disaster Recovery, Distributed Computing Environment, Distributed Systems, Document-Oriented Databases, Electronic Data Interchange (EDI), R (Programming Language), Identity and Access Management, Python (Programming Language), Machine Learning, Meta-Data Management, Performance Tuning, Role-Based Access Control, Cloud Services, Azure Data Lake, Software Engineering, SQL Databases, Virtual Machines, Workflow Management Systems, Parquet, Cloud Platform System, High Performance Computing, Azure Data Factory, System Availability, Database Optimization, Apache Spark, Electronic Medical Records, Git, Data Lakes, Semi-structured Data, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Health Level Seven International, Azure AKS, Machine Learning Operations, Data Lakehouse, Data Delivery, Azure Synapse Analytics, Software Version Control, Data Pipelines, Docker, Databricks - **Published:** August 11, 2026 - **Apply:** https://www.juju.com/job/00000000gmp1nm ## About the Role * Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field. * 5+ years of experience (Bachelor-level) or 3+ years of experience (Master/PhD-level) in a data engineering role with demonstrated expertise building and maintaining production-grade data pipelines. * Strong ETL experience and demonstrated ability to transform data from one data model to another, as well as the process of data standardization. * Strong proficiency in Python and SQL for data transformation, pipeline development, and automation. * Hands-on experience with Microsoft Azure data services (Azure Data Factory, Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, or equivalent). * Experience with ETL pipeline development and workflow orchestration tools (e.g., Apache Airflow, dbt, Azure Data Factory, or equivalent). * Experience with distributed computing and big data processing frameworks (e.g., Apache Spark, Databricks). * Strong understanding of data modeling, data warehousing concepts, and cloud storage formats (e.g., Parquet, Delta Lake). * Experience with version control (Git) and collaborative software engineering practices including code review and CI/CD. * Strong written and verbal communication skills; ability to collaborate effectively with both technical and non-technical stakeholders. Specialized Skills / Other Requirements *Collaborate with data scientists and biostatisticians to optimize data access patterns and delivery formats (e.g., Parquet, Delta Lake) for analytical and machine learning workloads. *Support HPC and large-scale batch processing requirements as the team's data volumes and computational needs grow. *Serve as a key technical interface with external data and analytics partners, coordinating on data delivery, integration standards, pipeline design, and platform interoperability. *Collaborate with external vendors and platform partners to define data exchange formats, APIs, and integration specifications that meet the team's analytical requirements. * Manage and document data access agreements, ingestion schedules, and data refresh cadences with external data providers. Specialized Skills / Other Requirements: *Experience in a database administration (DBA) capacity or having designed and built cloud-based data storage systems is a plus, including experience with validation, compliance monitoring, and ongoing maintenance of those systems. *Familiarity with provisioning and managing virtual machines and cloud compute resources in Microsoft Azure or equivalent cloud environments. *Master's degree or PhD in Computer Science, Data Engineering, or a related technical field is preferred. *Broader cloud platform experience across AWS and/or GCP in addition to Azure. *R programming experience. *Experience with HPC (High-Performance Computing) environments and large-scale batch processing workloads. *Familiarity with containerization and orchestration technologies (Docker, Kubernetes, Azure Kubernetes Service). *Experience supporting data science and machine learning teams, including MLOps pipeline development and model serving infrastructure. *Experience working with healthcare data (EHR, claims, chargemaster, administrative, or registry data). *Familiarity with healthcare data standards and clinical vocabularies (e.g., ICD, CPT4, LOINC, SNOMED CT) is a plus but not required. *Familiarity with clinical data models or observational research data standards (e.g., OMOP CDM) is a plus but not required. *Experience in a medical device, pharmaceutical, or life sciences data environment. *Strong organizational, communication, and documentation skills. *Ability to make independent decisions and take responsibility for own actions within a fast-moving environment. *Ability to collaborate effectively and participate in a team environment. *Excellent verbal and written communication skills. ## Description The Data Engineer is responsible for designing, building, and maintaining the data infrastructure and pipelines that power Teleflex's Clinical Evidence Generation function. This individual owns the full data engineering lifecycle, from pipeline architecture and cloud platform management through to ETL development, data quality assurance, and the delivery of analytics-ready data products. The ideal candidate is an experienced data engineer with strong cloud platform expertise (Azure preferred), a solid foundation in software engineering and big data technologies, and a track record of building reliable, scalable data systems in complex enterprise environments. Experience with database administration, cloud-based storage validation and compliance, and infrastructure provisioning is a plus. Experience with healthcare data or life sciences is also a plus but not required. This is a remote based position. Principal Responsibilities *Customer Experience - Representing Teleflex in a customer facing position is a tremendous responsibility and opportunity. All CMA colleagues are expected to perform with the highest levels of professionalism, service and ethics in order to strengthen the Teleflex brand and relationship with our customers. *Continuous Improvement - Demonstrates initiative and critical thinking to identify, prioritize process and performance gaps. Develops solutions to deliver improving results. Exemplifies continuous improvement thought processes and focus. *Culture and Values - Exemplifies Teleflex values and ensures a fair, open and productive climate that is engaging, ethical, and legally compliant. Strives to work effectively across boundaries in a complex matrix environment. *Design, build, and maintain scalable, production-grade data pipelines for the ingestion, transformation, and delivery of large-scale datasets from diverse source systems. *Develop and maintain ETL/ELT workflows that reliably move and transform data across source systems, cloud platforms, and analytical environments, including transformation from one data model to another and data standardization. *Monitor, troubleshoot, and optimize existing pipelines to ensure high availability, performance, and data integrity across all data products. *Implement and enforce data quality checks, validation frameworks, and anomaly detection to maintain confidence in all data products delivered to downstream consumers. *Maintain comprehensive technical documentation for all pipelines, data models, and data dictionaries. *Architect and manage cloud-based data infrastructure with a primary focus on Microsoft Azure (Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage), with working familiarity across other major cloud platforms (AWS, GCP) welcomed. *Provision, configure, and maintain cloud-based virtual machines and compute environments, ensuring resources are properly sized, secured, and compliant with enterprise standards. *Validate, monitor, and maintain cloud-based data storage systems to ensure ongoing compliance withdata governance, security, and regulatory requirements (HIPAA, data use agreements, enterprise security policies). *Design and manage data lakehouse and warehousing solutions, optimizing for query performance, storage efficiency, and cost management at scale. *Implement and manage workflow orchestration, scheduling, and dependency management for complex multi-step data pipelines. * Apply database administration (DBA) principles to the design, maintenance, and optimization of structured and semi-structured data stores, including performance tuning, indexing strategies, backup and recovery procedures, and access management. *Contribute to the team's data governance framework, including data cataloging, lineage tracking, metadata management, and role-based access control. *Ensure all data engineering activities comply with applicable data privacy and security requirements. *Identify and implement opportunities to improve data pipeline efficiency, reduce processing latency, and increase throughput across the data platform. *Apply data mining and profiling techniques to understand source data characteristics, surface data quality issues, and inform pipeline design decisions. *Develop reusable data transformation components, libraries, and templates to accelerate pipeline development and reduce duplication across the data platform. *Evaluate and adopt new tools, frameworks, and cloud services that can improve the reliability, scalability, or efficiency of the team's data infrastructure. *Design and operate data processing workflows for large-scale datasets, applying distributed computing frameworks (e.g., Apache Spark, Databricks) to handle big data workloads efficiently. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)