Data Platform Engineer

Overview

At Tactile Medical, we are building a modern, scalable data platform on Microsoft Fabric to support enterprise analytics, reporting, and future data capabilities. The Data Platform Engineer will play a critical role in maturing and operationalizing this platform, ensuring it is reliable, efficient, and easy for teams to use. This role is responsible for translating architectural standards into practical, reusable platform patterns, while improving performance, reliability, and cost efficiency. As a highly visible contributor within IT, the Data Platform Engineer will combine hands-on technical expertise with mentorship and cross-functional collaboration to enable data engineers and BI teams to deliver high-quality solutions at scale.

Accountabilities & Responsibilities

Microsoft Fabric Platform Enablement

• Design and maintain Microsoft Fabric workspace standards, including dev/test/prod environments and naming conventions
• Configure and support core platform components such as pipelines, datasets, semantic models, and Lakehouse architecture
• Develop and document reusable platform patterns and best practices to promote consistency and scalability
• Partner with the Data Architect to implement and operationalize enterprise architecture standards

Data Engineering & Platform Development

• Design, build, and maintain data pipelines to ingest, transform, and load data from multiple source systems
• Implement scalable data integration solutions across disparate systems
• Apply medallion architecture and other modern data engineering practices
• Contribute hands-on development to support platform and data delivery needs

Reliability, Operations & Observability

• Establish and maintain platform monitoring practices, including pipeline failures, dataset refreshes, and dependencies
• Configure alerts, dashboards, and runbooks to proactively identify and resolve issues
• Troubleshoot platform performance, reliability, and operational challenges
• Improve overall platform stability to ensure a consistent and trusted user experience

Security, Access & Cost Management

• Implement and maintain role-based access controls across workspaces and datasets
• Support onboarding, access changes, and offboarding through standardized processes
• Monitor and optimize platform usage, balancing cost, performance, and scalability
• Contribute to governance practices that ensure secure and responsible data usage

Collaboration, Mentorship & Enablement

• Mentor data engineers and technical team members on platform standards, patterns, and best practices
• Partner with cross-functional teams to support adoption and effective use of the data platform
• Communicate platform capabilities and constraints clearly to technical stakeholders
• Help establish processes and standards in a growing, evolving data environment

Other:

• Participate in platform and data strategy discussions
• Contribute to continuous improvement of engineering practices and platform capabilities
• Perform additional duties as assigned

Qualifications

Required:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent work experience)
• 5+ years of experience in data engineering, ETL development, or data platform engineering
• Experience working with Microsoft Fabric or related technologies (e.g., Azure Data Factory, OneLake, Synapse, Power BI)
• Strong hands-on experience building data pipelines (ETL/ELT) across multiple systems
• Experience implementing data integration and transformation solutions in a scalable environment

Preferred:

• Experience designing and implementing modern data architectures (e.g., medallion architecture, Lakehouse)
• Familiarity with enterprise data platforms supporting analytics and BI use cases
• Experience working in mid-sized organizations or environments requiring both hands-on work and strategic contribution
• Exposure to regulated industries such as healthcare or medical device

Knowledge & Skills

• Strong hands-on technical skills with the ability to design, build, and optimize data pipelines and platform components
• Deep understanding of data integration concepts, including ingestion, transformation, and loading from disparate systems
• Knowledge of platform reliability, monitoring, and operational best practices
• Ability to establish and enforce standards while remaining pragmatic and delivery-focused
• Experience mentoring others and elevating team capabilities through coaching and guidance
• Strong collaboration skills with the ability to work effectively across engineering, architecture, and analytics teams
• Clear and effective communicator with the ability to explain technical concepts to technical audiences
• High ownership mindset with the ability to build processes and standards in a growing environment
• Adaptable and solution-oriented, with a focus on continuous improvement and scalability