Analytics Engineer

Ensemble Health Partners • Work at Home - Ohio - Other, OH

1d • $84,000 - $126,000 • Remote

About The Position

The Analytics Engineer transforms curated data into clear, consistent, analytics-ready data models that power reporting, dashboards, and organizational decision-making. The position sits at the intersection of data engineering, analytics, and business, with responsibility for the semantic layer and for helping ensure metrics are trusted, well-defined, and easy to use. The ideal candidate has deep SQL transformation and dimensional modeling skills, strong business acumen, and an interest in enabling analysts and leaders with high-quality, intuitive data.

This is a remote position, but the employee must be willing and able to travel to and work onsite at client, temporary, or corporate office locations as business needs require. The role is limited to individuals who reside and are authorized to work in the United States.

Requirements

• Bachelor’s degree in Computer Science, Data Analytics, Statistics, Mathematics, or a related field, or equivalent experience.
• At least 3 years of experience in analytics engineering, analytics, business intelligence, or a related role.
• Advanced SQL expertise and a strong track record of building complex, maintainable transformations.
• Hands-on experience with dbt.
• Strong understanding of dimensional modeling, metrics design, and semantic layer concepts.
• Experience supporting BI tools and downstream analytics use cases, including dashboards, reporting, and ad hoc analysis.
• Ability to communicate clearly with technical and non-technical stakeholders.
• Experience in healthcare-related operations and understanding of industry processes and terminology.
• Inquisitiveness and openness to innovation, including AI, to explore better processes and ways to reduce friction and improve patient and client experiences.
• Must reside and be authorized to work in the United States.
• Must be willing and able to travel to and work onsite at client, temporary, or corporate offices as business needs require.

Nice To Haves

• Product or application engineering experience, with an understanding of data use in product and engineering applications.

Responsibilities

• Design, build, and maintain analytics-ready data models, including facts, dimensions, and data marts.
• Develop and manage transformations primarily in the semantic and transformation layer using SQL-based tooling.
• Define and maintain metrics, business logic, and calculations so they are consistent across dashboards, reports, and analyses.
• Apply dimensional modeling best practices for BI and analytical consumption.
• Partner with product, operations, finance, and business stakeholders to understand requirements and translate them into well-defined data models and metrics.
• Steward business logic by ensuring definitions are clear, documented, and aligned across teams.
• Identify gaps, ambiguities, or inconsistencies in metrics and drive alignment on standardized definitions.
• Optimize data models for clarity, usability, and performance for downstream consumers, including analysts and self-service BI users.
• Support analysts and BI developers in developing dashboards and reports more quickly and reliably.
• Ensure analytics outputs are intuitive, discoverable, and trusted by decision-makers.
• Implement analytics-layer data quality checks and testing to ensure accuracy and reliability.
• Contribute to analytics engineering standards, conventions, and documentation.
• Collaborate with data engineering partners and provide feedback on source data structure and readiness for analytics.

Benefits

• Comprehensive benefits package supporting physical, emotional, and financial health, including healthcare, time off, retirement, and well-being programs.
• Professional development and a relevant professional certification for each associate.
• Tuition reimbursement.
• Quarterly and annual incentive programs for employees who exceed expectations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level