Senior Analytics Engineer – AI & Data Engineering

Location: Remote
Duration: 9 Months Contract
Work Arrangement: Remote
Client: Boston University
Job Category: Data Engineering / Analytics Engineering / Artificial Intelligence

Job Overview

Sigma Systems is seeking an experienced Senior Analytics Engineer for a 9-month contract opportunity supporting Boston University.

This is an exciting opportunity for a senior-level Analytics Engineer or Data Engineer to design and build scalable, AI-ready data architectures that power enterprise reporting, advanced analytics, and artificial intelligence solutions.

The ideal candidate will bring extensive experience in SQL, Python, dbt, data modeling, semantic layers, cloud data architecture, and data pipeline orchestration. This professional will play a technical leadership role in developing trusted data models, enterprise metrics, and AI-ready data interfaces that enable Large Language Models (LLMs) and AI agents to reliably access and interpret institutional data.

Candidates with experience in modern data lakehouse technologies such as Apache Iceberg, Trino, AWS, and Dagster, along with emerging AI technologies such as RAG, embeddings, text-to-SQL, and Model Context Protocol (MCP), are highly encouraged to apply.

Key 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.

Technical Skills & Keywords

SQL | Python | dbt | Analytics Engineering | Data Engineering | Data Architecture | Data Modeling | Semantic Layer | Data Warehousing | Data Lakehouse | AWS | Amazon S3 | Apache Iceberg | Trino | Dagster | Git | CI/CD | Data Pipelines | Pipeline Orchestration | Data Governance | Metadata Management | Data Quality | Dimensional Modeling | Enterprise Metrics | AI Engineering | Artificial Intelligence | Machine Learning | LLM | Large Language Models | RAG | Retrieval-Augmented Generation | Embeddings | Text-to-SQL | MCP | Model Context Protocol | Context Engineering | Feature Engineering | Cloud Data Architecture

Ideal Candidate Backgrounds

We encourage applications from professionals currently working as:

• Senior Analytics Engineer
• Lead Analytics Engineer
• Senior Data Engineer
• Lead Data Engineer
• Analytics Architect
• Data Architect
• Senior dbt Developer
• Data Platform Engineer
• AI Data Engineer
• Machine Learning Data Engineer
• Cloud Data Engineer
• Data Engineering Technical Lead

Contract Details

• Job Title: Senior Analytics Engineer – AI & Data Engineering
• Client: Boston University
• Duration: 9 Months Contract
• Location: Remote
• Work Arrangement: Remote
• Experience Required: 8+ Years