Analytics Engineer

Analytics Engineer

KLS MARTIN LP - 2.9

Jacksonville, FL Job Details Full-time 1 day ago Benefits Paid parental leave Parental leave Qualifications Performance dashboard reports Data model design Dashboard development Power BI Data visualization software proficiency Technical documentation Writing skills Basic math Public speaking Data reporting Mid-level Data quality management Data Architecture Design (Architecture design skills) Team management Task prioritization Decision making Requirements analysis Product backlog management Natural language processing Scalability Data validation Workshop facilitation Business requirements Data analytics tools AI Data transformation Cross-functional collaboration Data-driven decision making Communication skills Technical Proficiency Project stakeholder communication Stakeholder relationship building Generative AI Cross-functional communication Dimensional modeling Stakeholder management Full Job Description 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.

Knowledge, Skills, and Abilities Data Modeling & Analytics Expertise:

Strong understanding of data modeling principles (e.g., granularity, metric definition, dimensional design) and ability to build scalable, reusable semantic models

Business Acumen & Problem Solving:

Ability to translate business needs into analytical solutions, think critically, and identify gaps, inconsistencies, and edge cases

Technical Proficiency:

Experience with modern analytics tools and data platforms, with preferred familiarity in the Microsoft ecosystem including Microsoft Power BI, Microsoft Fabric, and Azure Synapse Analytics, along with strong data querying and transformation skills

AI & Data Literacy:

Foundational understanding of AI-enabled analytics (e.g., natural language querying, automated insights) and ability to validate outputs for accuracy and relevance

Communication & Stakeholder Engagement:

Ability to clearly communicate insights and technical concepts to diverse audiences and effectively facilitate stakeholder collaboration

Visualization & User Experience:

Knowledge of data visualization best practices to design intuitive, user-friendly analytical experiences

Collaboration, Governance & Delivery:

Ability to work cross-functionally, manage priorities, and ensure data quality, consistency, and adherence to governance standards Skill Requirements Typing/computer keyboard Utilize computer software (specified above) Retrieve and compile information Verify data and information Organize and prioritize information/tasks Verbal communication Written communication Public speaking/group presentations Investigate, evaluate, recommend action Leadership and supervisory, managing people. Basic mathematical concepts (e.g. add, subtract) Abstract mathematical concepts (interpolation, inference, frequency, reliability, formulas, equations, statistics) Advanced mathematical concepts (fractions, decimals, ratios, percentages, graphs) Physical Requirements Sitting for extended periods Extended periods viewing computer screen Reading Speaking Hear/Listen Maintain regular, punctual attendance Bending/Stooping Reaching/Grasping Writing Hazards Normal office environment All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. At this time, we are not able to provide visa sponsorship or support employment authorization for this position. Candidates must be authorized to work in the United States without current or future sponsorship. KLS Martin is a drug free employer