Job DescriptionIn this role, you will lead the design of the analytics data architecture, semantic models, and pipelines that power university reporting, analytics, and AI solutions. Working at the intersection of analytics engineering, data engineering, and artificial intelligence, you will define the metrics, business logic, and context that enable large language models (LLMs) and AI agents to reliably understand and query institutional data, and you will bring software engineering rigor to modern data tools such as dbt, Dagster, Apache Iceberg, Trino, and AWS. As part of the AI, Automation, and Data Engineering team, you will report to the [Reporting Manager Title], serve as a technical leader on high-priority initiatives, mentor fellow engineers, and partner with data engineers, AI engineers, researchers, faculty, and staff in a hybrid work environment based in Boston, MA. This is an opportunity to help define an evolving discipline and build the data foundations that support university operations, research, and innovation. You Will: Architect and lead development of scalable analytics data models and lakehouse data layers using dbt, SQL, and Python. Define and govern the semantic layer, including enterprise metrics and business logic, as a single source of truth for reporting and AI. Lead context engineering efforts, designing the metadata, semantic models, and AI-ready interfaces (e.g., MCP, text-to-SQL) that enable LLMs and AI agents to accurately use institutional data, and measure their accuracy. Design production-grade data and ML pipelines, including feature engineering and embedding pipelines, using Dagster and AWS. Set engineering and data quality standards and conduct expert-level code reviews. Lead technical planning and delivery for cross-functional initiatives and contribute to IS&T's analytics and AI data strategy. Mentor engineers and foster a culture of engineering excellence.
Required SkillsYou Will Have:
- Bachelor's degree in computer science, Information Systems, Data Science, Data Analytics, or a related field (or equivalent combination of education and experience); advanced degree preferred.
- 8+ years of professional experience in analytics engineering, data engineering, or a related technical field, including technical leadership of complex projects.
- Expert SQL and Python skills, with extensive experience building data models and transformations using dbt or similar tools.
- Advanced software engineering practices, including Git, automated testing, CI/CD, code review, and pipeline orchestration.
- Deep expertise in data architecture, data modeling, and semantic layer design, including metrics frameworks and metadata management, in cloud lakehouse environments (e.g., S3, Apache Iceberg, Trino).
- Experience enabling AI and ML use cases with data, such as LLM integration, RAG, embeddings, text-to-SQL, or ML pipelines; familiarity with emerging standards such as MCP is desirable.
- Strong understanding of data governance, privacy, security, and compliance for sensitive institutional data.
- Excellent communication skills, with a proven track record of collaborating with technical and non-technical stakeholders, mentoring engineers, and leading technical initiatives.
Boston University offers an excellent benefits package including:
- Time Off: In addition to PTO and leave policy, BU employees have a paid intersession break and 13 paid holidays.
- Retirement: University-funded retirement plan with full vesting after 2 years of eligible service.
- Tuition Assistance Program: Competitive tuition assistance program for yourself and family members.
- Check out https://www.bu.edu/wellness/ and https://www.bu.edu/hr/part-time-employee-perks/ for more information!
Boston University IS&T invests in our staff and their personal and professional growth. We promote staff learning including lunch and learn sessions, an extensive library of online courses, Fun Advisory Board (FAB) arranges a number of events throughout the year and opportunities to engage with peers at NERCOMP and EDUCAUSE events.
