The Analytics Engineer role bridges data engineering and data analytics by delivering analytics-ready pipelines, semantic models, and enterprise data assets that support consistent metrics and KPIs. This position applies software engineering practices and collaborates across teams to translate business needs into reliable analytical solutions.

Key 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.

Required Qualifications

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.
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.

Technologies

dbt
dlt
Directed Acyclic Graphs (DAGs)
Strategy (BI)
Mosaic
Databricks
SQL Server
PostgreSQL
GitHub Copilot
Git
CI/CD
SQL
Python

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

Work Location and Schedule

This position is full-time and hybrid.
Selected candidate must come into the Home office in Morrisville on Wednesdays, for business meeting as needed.
Candidate must reside within 50 miles of Morrisville, North Carolina.

Compensation

Salary range: USD 83,510 - 106,475 per year.

Exact compensation will be determined based on education, experience, external market data, and internal equity considerations.

Analytics Engineer