Data Engineer

Description

Company Overview:

Biomerics is a world-class manufacturer and innovative polymer solutions provider for the medical device and biotech industries. As a vertically integrated company, we specialize in designing, developing, and producing medical devices for diagnostic and interventional procedures. We are focused on next-generation solutions for vascular access, electrophysiology, cardiac rhythm management, neurovascular, structural heart, and cardiovascular markets.

At Biomerics, we are dedicated to our diverse employee base. We understand that a strong, skilled, and engaged workforce is the foundation of our continued success as a business. We strive to live up to the Biomerics values in all our interactions. It is an exciting time to be part of our collective team. There is no limit to the impact that can be achieved here at Biomerics. We improve and advance our employees' and patients' lives that depend on our products.

At Biomerics we believe in integrity, partnership, empowerment & accountability, trust, agility, teamwork, excellence, and we care. Our team-oriented, customer-focused corporate culture places a premium on building strategic, mutually beneficial partnerships with customers and our team members.

Job Summary:

We are seeking a highly skilled and motivated Data Engineer to join our growing team. This position will play a pivotal role in designing, building, and maintaining our data infrastructure. Additionally, you will be pivotal in consolidating disparate data into a centralized Data Lakehouse/Warehouse used for enterprise analytics. As a Data Engineer, you will work with the latest data engineering technologies to develop robust data pipelines, ensure data availability, and support the organization in its data-driven initiatives. The ideal candidate will have a strong background in data engineering, experience with the Microsoft ecosystem, and a passion for developing scalable solutions. Experience with dbt (Data Build Tool) for transforming and modeling data is a must.

Requirements

Job Roles and Responsibilities:

· Design and Develop Data Pipelines: Build and manage complex data pipelines using Fabric Data Factory and Notebooks (among other tools) to support the flow of structured and unstructured data.

· Data Modeling: Create and maintain conceptual, logical, and physical data models using dbt (Data Build Tool) for transforming raw data into clean, structured datasets to support analytics, business intelligence, and data science use cases.

· Cloud Data Solutions: Architect, implement, and manage cloud-based solutions using Microsoft Fabric and Azure - ensuring optimal data storage, transformation, and retrieval processes.

· DevOps Integration: Utilize Azure DevOps to support Continuous Integration and Continuous Deployment (CI/CD) of data workflows and processes.

· Notebook-based Development: Work in Microsoft Fabric and Azure Synapse using notebooks for data engineering tasks and advanced data analysis.

· Machine Learning Integration: Collaborate with data scientists to deploy TensorFlow models and other machine learning solutions within data pipelines.

· Data Governance & Security: Implement and enforce data governance policies, ensuring compliance with security standards and data privacy regulations.

· Performance Optimization: Monitor and optimize the performance of data pipelines, databases, and models to ensure efficiency and scalability.

Job Qualifications:?

· Education:

o Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field. A Master’s degree is a plus.

· Experience:

o 5+ years of experience as a Data Engineer or similar role.

o Proven experience with Microsoft Azure and Microsoft Fabric data services, including Azure/Fabric Data Factory and Azure SQL.

o Hands-on experience with Microsoft Fabric, Power BI, Azure DevOps, and dbt (Data Build Tool) for data modeling and transformation.

o Familiarity with machine learning frameworks like TensorFlow and integrating them into data pipelines.

· Technical Skills:

o Highly proficient in SQL, Python, Spark, and other data processing languages.

o Experience with dbt for building and deploying data transformation workflows.

o Experience with cloud architecture, CI/CD pipelines, and data security best practices.

o Strong understanding of data modeling, Ralph Kimball Dimensional Modeling, stored procedures, ETL processes, and data warehouse architecture.

· Soft Skills:

o Excellent communication and collaboration skills.

o Strong problem-solving abilities and attention to detail.

o Ability to work independently as well as part of a cross-functional team.

Benefits:?Medical/Dental/Vision Insurance, Short-Term Disability, Long-Term Disabi