Systems Engineer

Systems Engineer

Location: Boston, MA

Onsite Flexibility: Remote

Contract Details

• Position Type: Contract
• Contract Duration: 9 months
• Pay Rate: $70.00 $75.00 / Hour (USD)
• Work Authorization: Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Job Summary

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. 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.

In 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, 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.

Key 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

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 Skills

• 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

Education 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

Required Experience

• 8+ years of professional experience in analytics engineering, data engineering, or a related technical field, including technical leadership of complex projects

Benefits

• Medical, Vision, and Dental Insurance Plans
• 401k Retirement Fund

About the Client

This client is a global research and teaching institution with campuses in Boston, Massachusetts, and academic programs spanning more than 30 countries worldwide. With nearly 38,000 students, more than 4,000 faculty members, and over 300 academic programs, it consistently ranks among the nation's top 50 universities and is a member of the Association of American Universities, placing it among the leading research institutions in the country. The organization received more than $574 million in sponsored research funding in a recent fiscal year and is rated 4.2 out of 5 stars on Glassdoor, with 89% of reviewers recommending it as a workplace. Teams here include faculty researchers, academic administrators, student affairs professionals, and technology and operations staff including software engineers, data engineers, analytics engineers, AI engineers, and institutional research professionals dedicated to education and discovery at the highest level.

About GTT

GTT is an NMSDC-certified Minority Business Enterprise (MBE) headquartered in Portsmouth, New Hampshire. GTT is a subsidiary of Chenega Corporation, an Alaska-based company and one of the largest Alaska Native-owned corporations. An Inc. 5000 honoree and one of SIA's Best Staffing Firms to Work For, GTT connects professionals with Fortune 500 organizations across IT, engineering, construction, utilities, life sciences, financial services, and healthcare throughout the U.S. and Canada. We're committed to diverse, inclusive workplaces and to placing people in roles where they can do their best work.

Job Number: 26-18503 Industry: Engineering

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