This Analytics Engineer role bridges data engineering and data analytics, delivering analytics-ready pipelines, semantic models, and enterprise data assets to support consistent metrics and KPIs. The position applies software engineering practices and involves collaboration across teams to translate business needs into reliable analytical solutions.
Responsibilities
Design, build, and manage scalable analytics pipelines that move data from raw sources to analytics-ready assets
Develop and maintain complex Directed Acyclic Graphs (DAGs) to support logical execution and dependency management
Execute advanced extract, load, and transform workflows tailored for analytics use cases, with emphasis on data cleansing, preparation, and transformation
Architect and manage semantic models using Strategy (BI) and Mosaic to provide a centralized source of business metrics
Design and scale data assets such as metrics stores, semantic layers, and analytical cubes to enable enterprise-wide self-service analytics
Use enterprise data platforms to process large-scale datasets and implement modern data engineering workflows in a cloud environment
Perform database management tasks for Strategy (BI) databases, ensuring environments are optimized and integrated with analytics pipelines
Use AI-augmented tools to speed up code development, documentation, and technical problem-solving
Apply responsible AI practices by crafting prompts and validating AI-generated code and outputs for accuracy and reliability
Partner with Data Analytics and Data Science teams to identify and deliver the specific data requirements and datasets needed for success
Collaborate with the Data Governance team to support secure, compliant, and high-quality enterprise data assets and products
Work with cross-departmental teams, including Quality Management and Medical Economics, to convert business needs into robust analytical solutions and data products
Apply software engineering disciplines across the analytics lifecycle, including version control, CI/CD, and automated orchestration
Integrate directly into domain teams to connect data management with business requirements and support federated analytics architectures
Requirements
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field from an accredited college/university, with at least three (3) years designing and operating data analytics pipelines
Experience designing, building, and managing scalable analytics pipelines in a modern data stack (including dbt and dlt) to transform raw data into analytics-ready assets
Expertise developing and maintaining complex Directed Acyclic Graphs (DAGs) for execution and dependency management
Millions of jobs, with real people getting hired every day
200,000+
New jobs added daily
7,000,000+
Verified job listings
1,000,000+
Tailored applications submitted
Semantic modeling experience, including architecting and managing semantic layers, metrics stores, and analytical cubes using Strategy and Mosaic
Proficiency leveraging Databricks and SQL Server to process large-scale datasets and implement cloud-based data engineering workflows
Proficiency managing PostgreSQL and SQL Server environments, including schema design, indexing, and performance tuning for analytics pipelines
Ability to use AI-driven tooling such as GitHub Copilot to accelerate code development, documentation, and technical problem-solving
Understanding of software engineering principles applied to analytics lifecycle workflows, including Git version control, CI/CD, and automated orchestration
Ability to translate complex business metrics and KPIs into technical artifacts while working with Data Science, Governance, Quality Management, and Medical Economics teams
Advanced skills in SQL and Python for sophisticated data manipulation, integration, and modeling
Benefits
Medical, Dental, Vision, Life, Long Term Disability
Generous retirement savings plan
Flexible work schedules including hybrid/remote options
Paid time off including vacation, sick leave, holiday, management leave
Dress flexibility
Important Details
Schedule: full-time
Work format: hybrid
Candidate must reside within 50 miles of Morrisville, North Carolina