Data Engineer

Overview As a Data Engineer, you will have the unique opportunity to design and establish a modern data engineering function within our organization. You will take the lead in building the data infrastructure that enables analytics, self‑service reporting, and AI‑ready data systems across the organization with Microsoft Fabric as a core platform. While you will operate with autonomy, you will also partner closely with data analysts, business stakeholders, development teams, and IT to modernize our hybrid on‑premises and cloud data environment. This is a hands‑on role with strategic influence—you will own the full engineering lifecycle, from assessing our current data landscape and identifying gaps, to designing and implementing pipelines, data warehouses, Fabric lakehouses, and standardized data products. You will have the opportunity to define best practices, establish patterns, and shape the infrastructure and culture of data engineering within Comfort Medical. Success in this role will require strong technical fundamentals, the ability to work independently while collaborating effectively across teams, and a forward‑thinking approach to building systems that scale with business needs. Major Areas of Accountability Assess the current data landscape, identify infrastructure gaps, and propose solutions aligned with business needs and technical best practices. Design and implement ETL/ELT pipelines including Microsoft Fabric, Synapse Spark, or modern equivalent platforms to build and maintain data warehouses, Fabric lakehouses, and lakehouse architectures that serve analytics, self‑service reporting, and AI use cases. Establish data quality standards and SLAs for availability, quality, and timeliness through automated validation, testing, monitoring, alerting, and incident response processes. Implement version control, CI/CD practices, and automated testing (unit, integration, data validation) to ensure reliable, safe deployment of data workflows. Utilize centralized data storage solutions such as OneLake or equivalent cloud architectures. Optimize pipelines and infrastructure for performance and cost efficiency. Develop robust documentation for data lineage, transformations, and system architecture to support governance and knowledge sharing. Self‑Service Analytics Enablement Collaborate with analysts to standardize and streamline Power BI and Fabric semantic models, reducing inconsistencies in reporting definitions. Create user‑friendly data products and views that enable non‑SQL‑fluent business users to self‑serve analytics. Implement modern data and analytics tools and frameworks (including Fabric's integrated capabilities) to ensure maintainability and scalability of data pipelines. Architecture & Strategic Planning Develop a data estate strategy that leverages Microsoft Fabric and modern data platforms, defining source systems, governance frameworks, integration patterns, and technology recommendations. Design infrastructure to support emerging AI and process automation initiatives, ensuring data is structured and governed for machine learning applications across the technology stack. Participate in technology evaluation and recommendation for tools, platforms, and methodologies that align with organizational goals (including Fabric capabilities). Mentor and guide analysts on modern data engineering best practices and emerging tools, including Fabric. Stakeholder Collaboration & Communication Partner with business stakeholders to understand data needs and translate them into technical requirements. Work closely with development teams and global IT on integration efforts, system upgrades, and infrastructure initiatives. Communicate technical decisions and architecture recommendations to both technical and non‑technical audiences. Serve as a subject matter expert on data engineering best practices and emerging technologies. Compliance & Ethics Comfort Medical employees are required to conduct business to the highest ethical and professional standards; comply with applicable laws and regulations, the MedTech Code of Conduct, and company policies. Basic Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Master's degree preferred. Minimum of 4+ years of experience in a data engineering, database, or infrastructure role, preferably in healthcare or regulated industries. Demonstrated experience designing and implementing ETL/ELT pipelines in production environments. Advanced proficiency in T‑SQL, relational database design, and performance optimization. Experience with cloud platforms (e.g., Azure) and hybrid on‑premises/cloud data environments. Hands‑on experience with modern data pipeline tools and platforms (e.g., Microsoft Fabric, Azure Data Factory, Synapse Spark, or equivalent). Strong Python programming skills for data processing, automation, and tooling including work in notebook environments. Experience with data warehousing and/or lakehouse architecture concepts. Familiarity with Business Intelligence tools (Power BI and Fabric semantic models experience a plus). Experience integrating with third‑party platforms (e.g., Salesforce APIs). Equal Employment Opportunity Comfort Medical is committed to a policy of Equal Employment Opportunity (EEO) which means we employ and promote individuals based on their merits, regardless of race, color, religion, sex, national origin, age, disability, veteran status, pregnancy, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, status with regards to public assistance or any other protected classification. #J-18808-Ljbffr