Analytics Engineer

About the role

The Analytics Engineer bridges the gap between data engineering and analytics by enriching available data sources, enabling new data products, building semantic models, and improving infrastructure to support scalable and governed analytics solutions. This role is critical in enabling self-service analytics and ensuring data quality and accessibility across SBA. The ideal candidate excels at translating complex business logic into enriched, reusable data products that empower business users to explore and analyze data independently, driving consistency and insight across the organization. This role is part of a collaborative, mission-driven team focused on elevating data maturity and enabling enterprise-wide analytics excellence. It also plays a foundational role in preparing enterprise data assets for consumption by AI and machine learning solutions, ensuring data is structured, enriched, and optimized for intelligent applications.

Responsibilities

• Design, build, and maintain robust semantic models and curated datasets that translate business logic into reusable, governed data products for self-service analytics and AI consumption.
• Develop and optimize data pipelines and dataflows to support scalable and performant analytics solutions across Microsoft Fabric, Power BI, Azure, and Databricks, with an emphasis on preparing clean, structured data for AI Agentic workflows.
• Collaborate with citizen developers and business stakeholders to understand analytical requirements and ensure semantic models and data products meet usability, accuracy, and compliance standards.
• Implement and manage row-level security (RLS) within semantic models to ensure appropriate data access and compliance with organizational policies.
• Develop and execute testing and validation strategies to ensure the accuracy, reliability, and consistency of data transformations and analytics outputs.
• Apply engineering best practices such as modular design, version control, and code documentation to analytics workflows.
• Document business logic, data transformations, and model structures in technical documentation, data dictionaries, and metadata catalogs, ensuring data lineage and feature clarity to support generative AI and predictive modeling initiatives.
• Design and implement automated data workflows and orchestration strategies to streamline model deployment, ensure timely data availability, and support scalable analytics operations.
• Support coordination with contractors and internal teams to align on data architecture, modeling standards, and delivery timelines.
• Promote adoption of self-service analytics tools by enabling business users and ensuring data products are intuitive, well-documented, and aligned with user needs.
• Other duties as required.

Requirements

Bachelor’s or Master’s degree in Data Engineering, Computer Science, Information Systems, a related field, or equivalent experience.

Minimum of 3 years of experience in analytics engineering, data modeling, or business intelligence development.

Skills

• Advanced proficiency in SQL, DAX, and Power BI, with demonstrated experience building and optimizing semantic models and dataflows.