Analytics Engineer

Sigma Systems, Inc.; Boston (MA); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Sigma Inc. is seeking an Analytics Engineer III to design, develop, and maintain analytics-ready data models, semantic layers, and data pipelines that support reporting, analytics, and AI-enabled solutions.

The role sits at the intersection of analytics engineering, data engineering, and AI, applying software engineering principles to transform raw data into well-documented data products that drive trusted insights. Remote/hybrid work with local Boston onsite as needed.

Qualifications

• Bachelor's degree in CS/IS/Data Science or equivalent
• 5+ years in analytics engineering or data engineering
• Strong SQL and Python skills
• Experience with dbt or similar data transformation tools
• Experience with data models and data architecture

Responsibilities

• Design and maintain analytics-ready data models and transformations using dbt, SQL, and Python
• Implement semantic layer definitions for reporting and AI apps
• Create metadata and data context for LLMs and AI agents
• Build and support orchestrated data pipelines
• Develop features and embeddings for ML analytics
• Apply data quality testing, contracts, and observability
• Adhere to Git, code reviews, automated tests, and CI/CD
• Collaborate with stakeholders to translate requirements into data solutions
• Contribute to data architecture and technical design

Skills

SQL

Python

dbt

Git

CI/CD

Data Modeling

Data Governance

Communication

Collaboration

Education

Bachelor's degree in CS/IS/Data Science

Tools

Amazon S3

Apache Iceberg

Trino

Job description

Analytics Engineer III

Job Title: Analytics Engineer III
Job ID: 1007
Location: Boston, MA
Job Type: Full-Time
Work Arrangement: Remote/Hybrid – Preference for candidates local to Boston who can come onsite as needed

Position Summary

Sigma Inc. is seeking an experienced Analytics Engineer III to design, develop, and maintain analytics-ready data models, semantic layers, and data pipelines that support reporting, advanced analytics, and AI-enabled solutions.

This role sits at the intersection of analytics engineering, data engineering, and artificial intelligence, applying software engineering principles to transform raw data into trusted, well-documented, reusable data products. The position will also help provide the governed business context needed for accurate AI analytics, AI agents, and machine learning workflows.

The Analytics Engineer III will work independently on complex technical assignments, contribute to data architecture and solution design, and collaborate with data engineering, AI engineering, and business teams. The role does not include formal supervisory responsibilities but may provide technical guidance and knowledge sharing within project teams.

Key Responsibilities

• Design, build, test, and maintain analytics-ready data models and transformations using dbt, SQL, and Python.
• Implement metrics and business logic within a semantic layer to establish consistent and trusted definitions across reporting and AI applications.
• Develop metadata, documentation, and structured data context that enables LLMs and AI agents to accurately interpret and query organizational data.
• Build and support orchestrated data pipelines.
• Develop curated datasets, features, and embeddings for machine learning and AI analytics.
• Implement data quality testing, data contracts, and observability processes to ensure data accuracy and reliability.
• Apply software engineering best practices, including Git, code reviews, automated testing, and CI/CD.
• Collaborate with stakeholders to translate business and research requirements into scalable data solutions.
• Contribute to data architecture, data modeling, and technical solution design.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics, or a related field, or an equivalent combination of education and experience.
• 5+ years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical field.
• Advanced SQL and Python skills.
• Hands‑on experience building data models and transformations using dbt or similar data transformation tools.
• Experience with software engineering practices, including:
  • Git/version control
  • Code review
  • Automated testing
  • CI/CD
  • Data pipeline orchestration
• Experience with data modeling and data architecture.
• Experience implementing semantic layers in cloud-based lakehouse environments.
• Experience with technologies such as Amazon S3, Apache Iceberg, and Trino is highly relevant.
• Ability to independently analyze technical requirements and deliver complex solutions with minimal supervision.
• Strong communication and collaboration skills.
• Solid understanding of data governance, privacy, and security best practices.

Preferred Qualifications

• Exposure to Large Language Models (LLMs).
• Experience with Retrieval‑Augmented Generation (RAG).
• Experience working with embeddings.
• Experience supporting AI‑driven analytics or AI agents.
• Experience delivering data products for machine learning applications.