Analytics Engineer

Key Responsibilities

Data Modeling & Semantics

• Build and maintain curated analytical datasets that feed reports and dashboards using Microsoft Fabric
• Apply established dimensional modeling patterns (facts, dimensions, shared measures) under guidance
• Help reduce report specific logic by contributing to centralized models and metric definitions
• Support consistency and reuse across analytics use cases by following modeling standards

Data Quality & Usability

• Validate modeled data against documented business expectations and known benchmarks
• Partner with BI developers to ensure datasets support reporting and visualization needs
• Identify downstream data issues related to modeling or logic and escalate for resolution
• Improve clarity and usability of datasets through consistent naming and structure

Architecture & Governance Alignment

• Apply modeling standards and patterns defined by the Data Architect and Analytics Engineering leads
• Align datasets with governance requirements such as:
• Shared definitions
• Certification status
• Approved usage patterns
• Support data discoverability by contributing to consistent dataset structures and documentation

Requirements

• 3-5 years of experience in data analytics, data engineering, reporting, or a related field.
• Demonstrated ability to design and implement data solutions using SQL or similar technologies.
• Strong ability to work directly with business stakeholders to gather requirements, communicate insights, and deliver data-driven solutions.
• Hands-on experience developing analytics, reporting, or data solutions. This role requires active execution and ownership rather than delegation of technical work.

Preferred

• Experience in healthcare, durable medical equipment (DME), or related health services industry
• Fabric engineering certification or willingness to obtain certification within 6 months of employment

Key Skills: Technical

• Designs analytics ready data models in Microsoft Fabric using SQL across Lakehouse and Warehouse
• Applies dimensional and semantic modeling independently to deliver consistent, reusable metrics
• Develops intermediate DAX measures to ensure correct metric behavior across reports
• Uses Power Query (M) to standardize data shaping and reduce duplication
• Validates and reconciles analytical datasets proactively to ensure accuracy before consumption

Professional

• Ownership mindset for analytical correctness and usability
• Willingness to learn, iterate, and improve existing models
• Collaborates closely with business users, ETL engineers, and governance roles
• Comfortable receiving feedback and working within defined standards

Measured Success

• Curated datasets are reused across multiple reports
• Metrics behave consistently across tools and dashboards
• BI teams rely on shared models rather than recreating logic
• Analytics datasets are easy to understand and trusted by users

Additional information

Our total compensation package includes medical, dental and vision benefits, retirement benefits, employee stock purchase plan, paid time off, parental leave, family medical leave, volunteer time off and additional leave programs, life insurance, disability coverage, and other life and work wellness benefits and discounts. Benefits may be subject to generally applicable eligibility, waiting period, contributions, and other requirements and conditions.

Pay and benefits

Below is the starting salary or hourly range for this position, although offers may differ based on the candidate's location, job-specific knowledge, skills and experience.

US Pay Range $93,600—$131,040 USD