Analytics Engineer

Analytics Engineer III – Boston, MA

Sigma Inc. is seeking an experienced Analytics Engineer III to join a data and analytics team supporting Boston University. This opportunity is ideal for an Analytics Engineer, Data Engineer, or BI/Data professional with strong SQL, Python, dbt, data modeling, semantic layer, and data pipeline experience.

The Analytics Engineer III will transform raw data into trusted, documented, and reusable analytics data products that support reporting, business intelligence, advanced analytics, artificial intelligence (AI), machine learning (ML), and AI-enabled applications. The role works closely with data engineering, AI engineering, and university business stakeholders to develop reliable and governed data solutions.

Key Responsibilities

• Design, build, test, and maintain analytics-ready data models and transformations using dbt, SQL, and Python.
• Develop and maintain semantic layers, metrics, and business logic to provide consistent and trusted definitions across reporting and AI applications.
• Create metadata, documentation, and structured business context that enables LLMs and AI agents to accurately interpret and query institutional data.
• Build and support orchestrated data pipelines and curated datasets for analytics, machine learning, and AI applications.
• Develop and support features and embeddings for ML and AI-enabled analytics.
• Implement data quality tests, data contracts, and observability to improve data accuracy and reliability.
• Apply software engineering best practices, including Git, code reviews, automated testing, and CI/CD.
• Collaborate with technical and non-technical stakeholders to translate business and research requirements into effective data solutions.
• Work independently on complex technical assignments with minimal oversight.
• Contribute to data architecture and solution design initiatives.
• Follow data governance, privacy, security, and compliance best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics, or a related technical field; equivalent education and experience may be considered.
• 5+ years of professional experience in: Analytics Engineering, Data Engineering, Business Intelligence Development, Data Analytics, or a related technical discipline.
• Advanced SQL and Python skills.
• Experience building data models and transformations using dbt or similar technologies.
• Experience with software engineering practices, including: Git / version control, code review, automated testing, CI/CD, data pipeline orchestration.
• Experience with data modeling, data architecture, and semantic layer implementation.
• Experience working with cloud-based lakehouse/data platforms, such as: AWS / S3, Apache Iceberg, Trino.
• Ability to independently analyze technical requirements and deliver complex data solutions.
• Strong communication and stakeholder collaboration skills.
• Understanding of data governance, privacy, security, and data quality best practices.

Preferred / Nice-to-Have Experience

Experience with any of the following is highly desirable:

• LLMs / Large Language Models
• Generative AI
• RAG / Retrieval-Augmented Generation
• AI-driven analytics
• AI agents
• Embeddings
• Text-to-SQL
• Machine learning data pipelines
• Semantic modeling
• Metrics frameworks
• Metadata management
• Data contracts
• Data observability
• Cloud data engineering
• Lakehouse architecture