Who We Are

At KLS Martin, we offer a unique opportunity to contribute to the success of a dynamic and thriving company whose products are used daily across the world to help surgical patients. 

The KLS Martin Group is a worldwide leader in creating surgical solutions for the craniomaxillofacial and cardiothoracic fields. Surgical innovation is our passion, and we are constantly working with surgeons to improve surgical care for their patients. Our product portfolio includes titanium and resorbable implants for reconstruction, innovative distraction devices to stimulate bone lengthening, over 4,000 surgical instruments, and other surgical products designed specifically for CMF and cardiothoracic surgeons. 

KLS Martin is an innovative leader in the treatment of CMF deformities and trauma cases. We use Individual Patient Solutions (IPS) by using our proprietary IPS products where CT scans are used to custom design implants that are created specifically for that individual patient.  This technology allows our surgeons to provide the best-in-class treatment for their patients.

KLS Martin Guiding Principles

• Established, Privately Held Business Group: Responsive to customers, not shareholders. KLS Martin has manufactured medical products since 1896, and we have sold our products in the United States under the KLS name since 1993. We have always been, and always will be, privately owned.


• Patient Focus: We design products with the patient in mind CMF, Thoracic & Hand


• Product to Table: Integrated planning, design, manufacturing and distribution process


• Educational Partner: Our primary focus for support is on education


• Inventory Alliance: Inventory management is critical to patient treatment/outcome


• Surgical Innovation is Our Passion: More than just a tagline

What We Offer

• We provide full-time employees with a competitive benefits package, including paid parental leave


• In-house training and professional development opportunities 


• A culture of creativity and innovation by drawing on diverse perspectives and ideas to drive surgical innovation

 

Job Summary

The Analytics Engineer serves as the primary interface between business stakeholders and the data platform, responsible for translating business needs into scalable, governed, and insight-driven analytical solutions. This role owns the end-to-end lifecycle of analytics delivery – from requirements elicitation and semantic modeling to insight generation and user adoption.

Operating within a modern data ecosystem, the Analytics Engineer designs reusable data models, develops intuitive analytical experiences, and ensures consistent metric definitions across the organization. The role emphasizes a product-oriented mindset, treating analytics assets as long-lived, evolving products rather than one-time deliverables.

As data platforms increasingly incorporate artificial intelligence, this role is also responsible for leveraging AI-enabled capabilities (e.g., natural language querying, automated insights, copilots) and ensuring that AI-generated outputs are accurate, governed, and aligned with business semantics.

 

Essential Functions, Duties, and Responsibilities

Business Engagement & Requirements Engineering

• Partner with stakeholders to translate ambiguous business questions into structured analytical requirements


• Facilitate workshops to define KPIs, metrics, dimensions, grain, and business rules


• Challenge and refine requirements to align with decision-making objectives rather than surface-level reporting requests


• Document definitions, assumptions, and data logic to ensure transparency and consistency

Semantic Modeling & Data Design

• Design and maintain reusable, scalable semantic models aligned with business processes


• Define and standardize core metrics, ensuring consistency across analytical outputs


• Apply sound data modeling principles (e.g., dimensional modeling, normalization vs denormalization trade-offs)


• Ensure models are optimized for performance, usability, and extensibility

Analytics Development & Delivery

• Develop and deliver analytical assets (dashboards, reports, data products, self-service datasets)


• Structure solutions with clear separation between data, semantic, and presentation layers


• Apply best practices in data transformation, calculation logic, and visualization design


• Ensure solutions are intuitive, performant, and aligned with user workflows

AI-Augmented Analytics & Innovation

• Leverage AI-enabled capabilities (e.g., natural language interfaces, automated insights, generative copilots) to enhance analytics development and consumption


• Validate and govern AI-generated insights, ensuring alignment with enterprise data definitions and quality standards


• Identify opportunities to embed predictive or prescriptive insights into analytics experiences


• Educate stakeholders on responsible and effective use of AI-driven analytics features

Data Quality, Validation & Governance

• Validate analytical outputs against source systems and business expectations


• Identify and resolve data quality issues, including inconsistencies in definitions or logic


• Adhere to enterprise governance standards for naming, documentation, and metric certification


• Prevent duplication of logic and ensure a “single version of truth” across analytics assets

Stakeholder Communication & Adoption

• Communicate insights and technical concepts effectively to both technical and non-technical audiences


• Guide stakeholders in interpreting data and using analytical tools effectively


• Drive adoption of analytics solutions through training, documentation, and iterative improvements


• Act as a trusted advisor for data-driven decision-making

Collaboration with Data Engineering Team

• Partner with data engineering team to define data requirements (e.g., granularity, latency, transformations)


• Provide feedback on upstream data structures to improve downstream analytics usability


• Align with platform architecture, performance constraints, and data lifecycle management practices

Product Mindset & Continuous Improvement

• Manage analytics solutions as products, including backlog prioritization, iteration, and enhancement


• Continuously evaluate and improve existing assets for performance, usability, and business impact


• Stay current with emerging trends in analytics, data platforms, and AI capabilities

The above cited duties and responsibilities describe the general nature and level of work performed by people assigned to job. They are not intended to be an exhaustive list of all the duties and responsibilities that an incumbent may be expected or asked to perform.