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Senior Analytics Engineer

Job in Durham, Durham County, North Carolina, 27703, USA
Listing for: Harnham
Full Time position
Listed on 2026-05-31
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Business Systems/ Tech Analyst, Data Engineering
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Role Overview

We are seeking a Senior Analytics Engineer to join a growing Analytics Delivery organization. This role focuses on designing and owning the semantic and metrics layer that powers business intelligence, self-service analytics, and emerging AI/LLM-driven analytics tools.

This is a highly technical, business-facing role centered on data modeling, transformation, and business logic. It is not a dashboard or report development position. You will operate at the intersection of data engineering, analytics, and business context, ensuring analytical data is scalable, reliable, and interpretable by both humans and AI systems.

Key Responsibilities
  • Build and maintain dbt data models and transformations
  • Design, define, and own the semantic and metrics layer
  • Translate business questions into scalable, well-defined analytics models
  • Establish clean, consistent, and trusted metric definitions
  • Structure data to support BI tools, self-service analytics, and AI/LLM-driven querying
  • Collaborate closely with business stakeholders, BI developers, and data engineering teams
  • Ensure analytics models follow best practices for scalability, documentation, and reuse
Required Experience and Qualifications
  • 6–8+ years of total professional experience
  • Background typically includes 3+ years in data engineering and 3+ years in analytics engineering or advanced BI work
  • Strong healthcare data experience preferred, including medical claims data, EHR/EMR systems, and familiarity with HL7 and FHIR
  • Understanding of clinical data versus transactional healthcare data
Technical Skills
  • Advanced SQL skills
  • Strong hands-on experience with dbt, including macros, snapshots, exposures, and metrics layers
  • Deep understanding of data modeling principles, semantic layers, and translating business logic into analytics-ready datasets
Nice-to-Have Experience
  • Snowflake
  • Databricks or Spark
  • Looker or LookML
  • Semantic layer tools such as AtScale or Cube
  • Thought Spot or Sigma, especially for AI-driven or agentic BI
  • Microsoft Fabric
  • Prefect, Monte Carlo, or similar data reliability tooling
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Position Requirements
10+ Years work experience
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