Analytics Engineer III – Data Engineering, dbt, SQL & Python

Job Title: Analytics Engineer III
Job ID: 1007
Location: Boston, MA
Duration: 12 Months Contract
Work Arrangement: Remote/Hybrid – Preference for candidates local to Boston who can come onsite as needed

Position Overview

Sigma Inc. is seeking an experienced Analytics Engineer III to design, develop, and maintain analytics-ready data models, semantic layers, and data pipelines that power business intelligence, reporting, advanced analytics, AI applications, and machine learning workflows.

This role combines analytics engineering, data engineering, software engineering, and AI. The ideal candidate will have strong hands-on experience with SQL, Python, dbt, data modeling, cloud data platforms, data pipelines, and modern software engineering practices.

The Analytics Engineer III will work independently on complex technical initiatives, contribute to data architecture and solution design, and collaborate with data engineering, AI engineering, and business teams to build trusted and reusable data products.

Key Responsibilities

• Design, build, test, and maintain analytics-ready data models and transformations using dbt, SQL, and Python.
• Develop and maintain semantic layers, metrics, and business logic to provide consistent definitions across reporting and AI applications.
• Build and support orchestrated data pipelines and curated datasets for analytics and machine learning.
• Develop metadata, documentation, and structured data context that enables LLMs and AI agents to accurately interpret and query organizational data.
• Develop and support features, embeddings, and AI-ready datasets for machine learning and AI analytics.
• Implement data quality testing, data contracts, and observability to improve data accuracy and reliability.
• Follow software engineering best practices, including Git, version control, code reviews, automated testing, and CI/CD.
• Contribute to data architecture, data modeling, and technical solution design.
• Partner with stakeholders to translate business and research requirements into scalable data solutions.
• Work independently to analyze technical requirements and deliver complex data solutions with minimal oversight.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics, or a related field, or equivalent education and experience.
• 5+ years of professional experience in analytics engineering, data engineering, business intelligence development, or a related technical field.
• Advanced proficiency in SQL and Python.
• Hands-on experience with dbt or similar data transformation and modeling tools.
• Strong experience with data modeling and data architecture.
• Experience implementing semantic layers and business metrics.
• Experience with software engineering practices, including:
  • Git/version control
  • Code reviews
  • Automated testing
  • CI/CD
  • Data pipeline orchestration
• Experience working with cloud-based lakehouse environments.
• Experience with technologies such as Amazon S3, Apache Iceberg, and Trino.
• Understanding of data governance, privacy, security, and data quality best practices.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Ability to independently deliver complex technical solutions.

Preferred Qualifications

• Experience with Large Language Models (LLMs).
• Knowledge of Retrieval-Augmented Generation (RAG).
• Experience working with embeddings.
• Experience supporting AI-driven analytics or AI agents.
• Experience developing data products for machine learning and AI applications.
• Experience working with modern cloud data and analytics architectures.