Senior Analytics Engineer

Job Title: Senior Analytics Engineer
Location: Boston, MA
Type: Contract
Compensation: $68-$73.33/hr
Work Model: Remote
Hours: 8am to 5pm MF

Overview
The Senior Analytics Engineer leads the design and development of the analytics data architecture, semantic models, and data pipelines that power reporting, analytics, and AI-enabled solutions at the company. Operating at the intersection of analytics engineering, data engineering, data architecture, and artificial intelligence, this role applies advanced software engineering principles to deliver trusted, reusable data products and defines the governed semantic and contextual foundation that enables accurate AI analytics, agents, and machine learning workflows across the university

The Senior Analytics Engineer serves as a technical lead on complex, high-priority initiatives, establishes standards and best practices for analytics engineering, and partners with data engineering, AI engineering, and institutional stakeholders to shape the university’s data and AI strategy. As analytics, data, and AI disciplines continue to converge, this role is expected to help define how analytics engineering evolves within IS&T. This role does not include formal supervisory responsibilities but provides technical leadership, mentorship, and guidance to other engineers.

Responsibilities

• Analytics Data Architecture & Modeling (30%)
  • Architect, design, and lead the development of scalable, analytics-ready data models and data products.
  • Lead the design of enterprise data models and layered lakehouse architectures using dbt, SQL, and Python on platforms such as S3, Apache Iceberg, and Trino
  • Define modeling patterns and standards that ensure consistency, reusability, and performance, and resolve complex data design and scalability challenges
  • Partner with Data Architects and Data Engineers on data architecture, integration patterns, and platform design decisions
• Semantic Layer & Context Engineering (25%)
  • Lead the design and implementation of the semantic and context layers that connect university data to people and AI systems.
  • Architect and govern the semantic layer, including enterprise metrics, business logic, and entity relationships, as a single source of truth for reporting and AI applications
  • Design context engineering approaches (e.g., semantic models, knowledge graphs, metadata, retrieval strategies) and AI-ready data interfaces (e.g., MCP, text-to-SQL) in partnership with AI Engineering
  • Establish evaluation frameworks to measure and improve the accuracy and trustworthiness of AI-driven analytics
• Data, AI Analytics & ML Pipeline Engineering (20%)
  • Design and deliver production-grade pipelines that support analytics, machine learning, and AI solutions.
  • Architect and optimize orchestrated batch and event-driven data pipelines using Dagster and AWS services
  • Design pipelines for feature engineering, model training and scoring, and embedding generation that support ML models, RAG, and AI analytics
  • Ensure operational reliability through monitoring, alerting, and lifecycle management of production pipelines
• Engineering Standards, Quality & Governance (10%)
  • Define and champion software engineering and data quality standards for analytics engineering.
  • Establish standards for version control, testing, CI/CD, and documentation, and conduct expert-level code reviews
  • Implement enterprise-grade data quality frameworks, data contracts, lineage, and observability
  • Ensure alignment with university data governance, privacy, security, and compliance requirements, including the responsible use of data in AI applications
• Technical Leadership, Collaboration & Mentorship (15%)
  • Serve as a technical leader and trusted partner across IS&T and the university.
  • Lead technical planning and delivery of complex, cross-functional initiatives, partnering with Data Engineering, AI Engineering, Institutional Research, and business units to align data products with institutional priorities
  • Mentor engineers through design and code reviews, and lead knowledge sharing and team development
  • Evaluate emerging tools and practices and contribute to the roadmap for analytics engineering and AI-ready data within IS&T

Requirements

• 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.

System One, and its subsidiaries including Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan.

System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law.

Ref: #558-Scientific