Remote Analytics Engineer

BOSU3741 Remote Analytics Engineer III 9 Months

Summary:

Join us as an Analytics Engineer III where you will design, develop, and maintain the data models, semantic layers, and pipelines that turn university data into trusted, AI-ready data products. Working at the intersection of analytics engineering, data engineering, and artificial intelligence, you will apply software engineering practices to modern data tools such as dbt, Dagster, Apache Iceberg, Trino, and AWS, and help build the business context that allows large language models (LLMs) and AI agents to understand and accurately answer questions about university data. As part of the AI, Automation, and Data Engineering team, you will report to the [Reporting Manager Title] and work closely with data engineers, AI engineers, analysts, faculty, and staff in a hybrid work environment based in Boston, MA

Responsibilities

• Design, build, test, and maintain analytics-ready data models and transformations using dbt, SQL, and Python.
• Implement metrics and business logic within a semantic layer to ensure consistent, trusted definitions across reporting tools and AI applications.
• Develop metadata, documentation, and structured context that enables LLMs and AI agents to accurately interpret and query university data.
• Build and support orchestrated data pipelines, and deliver curated datasets, features, and embeddings for machine learning and AI analytics.
• Implement data quality tests, data contracts, and observability to ensure accuracy and reliability
• Apply software engineering best practices, including version control, code review, automated testing, and CI/CD.
• Partner with stakeholders to translate business and research needs into data solutions.

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics, or a related field (or equivalent combination of education and experience).
• 5+ years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical field
• Advanced SQL and Python skills, with experience building data models and transformations using dbt or similar tools.
• Experience with software engineering practices, including Git, code review, automated testing, CI/CD, and pipeline orchestration.
• Experience with data modeling, data architecture, and semantic layer implementation in cloud lakehouse environments (e.g., S3, Apache Iceberg, Trino).
• Exposure to LLMs, RAG, embeddings, or AI-driven analytics is desirable.
• Ability to analyze technical requirements and independently deliver complex solutions with minimal oversight.
• Strong communication skills and a solid understanding of data governance, privacy, and security best practices.