Remote Senior Analytics Engineer

Sigma Systems is seeking a Senior Analytics Engineer to support Boston University on a 9-month contract. The role leads the development of scalable analytics and lakehouse data architectures, trusted data models, and AI-ready interfaces and pipelines.

Responsibilities:

• Architect and lead the development of scalable analytics data models and modern lakehouse data layers using dbt, SQL, and Python
• Design, develop, and maintain enterprise data models and transformation pipelines to support reporting, analytics, and AI applications
• Define and govern semantic layers, enterprise metrics, business logic, and metadata management to establish a trusted single source of truth
• Develop AI-ready data architectures and interfaces that allow LLMs and AI agents to accurately interpret and query institutional data
• Lead context engineering initiatives involving semantic models, metadata, MCP, and text-to-SQL capabilities
• Design and implement production-grade data and ML pipelines, including feature engineering and embedding pipelines
• Utilize Dagster and AWS to orchestrate, deploy, and manage scalable data workflows
• Establish data engineering standards, data quality practices, automated testing, and software development best practices
• Conduct advanced code reviews and ensure the reliability, scalability, and maintainability of analytics solutions
• Lead technical planning and delivery of cross-functional data and AI initiatives
• Collaborate with data engineers, AI engineers, researchers, faculty, and business stakeholders
• Mentor engineers and provide technical guidance to promote engineering excellence
• Contribute to the organization's long-term analytics engineering, data architecture, and AI strategy

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics, or a related technical field, or equivalent professional experience

• 8+ years of professional experience in Analytics Engineering, Data Engineering, or a related technical discipline

• Demonstrated experience leading complex data engineering or analytics engineering projects

• Expert-level SQL and Python programming skills

• Extensive experience building data models, transformations, and analytics workflows using dbt or similar technologies

• Strong knowledge of data architecture, dimensional modeling, data warehousing, and semantic layer design

• Experience with modern cloud data platforms and lakehouse architectures

• Strong understanding of Git, automated testing, CI/CD, code reviews, and data pipeline orchestration

• Experience designing and maintaining production-grade data pipelines

• Experience with data governance, data quality, metadata management, privacy, and security

• Strong communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders

• Proven experience mentoring engineers and providing technical leadership

• Experience with AWS cloud services, particularly Amazon S3

• Hands-on experience with Apache Iceberg and Trino

• Experience with dbt Core or dbt Cloud

• Experience with Dagster or similar orchestration tools

• Experience designing and implementing semantic layers and enterprise metrics frameworks

• Experience supporting AI/ML initiatives involving:

  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Embeddings and vector-based search
  • Text-to-SQL applications
  • AI agents and AI-ready data interfaces
  • Model Context Protocol (MCP)

• Experience with feature engineering and machine learning pipelines

• Advanced degree in Computer Science, Data Science, Analytics, or a related discipline

• Experience working with large institutional, research, or enterprise datasets