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Analytics Engineer

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Hybrid

Analytics Engineer

RemyCorporation

Analytics Engineer

Skills

SQL QueriesData EngineeringPythonData ScienceGitData AnalysisMachine LearningAIdbt

17 days ago

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Important information


Contract type:

Permanent

Location:

Boston, MA, USA

Work mode:

Hybrid

Published on:

6 October 2026

What they need


This is a perm opportunity with our client in the greater Boston area. Must be able to work in a perm role without sponsorship. Must be local and able to work a hybrid schedule.

Please no 3rd party calls

Senior Analytics Engineer

Overview

We are seeking a Senior Analytics Engineer to lead the design and development of scalable analytics data models, semantic frameworks, and data pipelines that support enterprise reporting, analytics, and data-driven decision making.

This role sits at the intersection of analytics engineering, data engineering, data architecture, and emerging AI technologies. The ideal candidate will help build trusted, reusable data products while establishing standards and best practices that enable consistent reporting, advanced analytics, and future AI initiatives.

The Senior Analytics Engineer will serve as a technical leader on complex initiatives, collaborating with engineering teams, business stakeholders, and leadership to shape the organization's analytics strategy. This position provides technical mentorship and architectural guidance but does not include direct people management responsibilities.

Responsibilities

  • Architect and develop scalable analytics-ready data models and data products.
  • Architect and lead development of scalable analytics data models and lakehouse data layers using dbt, SQL, and Python.
  • Design and maintain enterprise semantic models, metrics, and business logic that serve as a trusted source for analytics and reporting.
  • Build and optimize data transformation pipelines using SQL, Python, and modern analytics engineering tools.
  • Partner with data engineering teams to design lakehouse and cloud data architectures.
  • Develop and support data pipelines that enable analytics, machine learning, and AI-driven use cases.
  • Establish best practices for data quality, testing, version control, CI/CD, documentation, and governance.
  • Implement data observability, lineage, and monitoring capabilities.
  • Lead technical design discussions and provide guidance on architecture and engineering standards.
  • Mentor engineers through code reviews, design reviews, and knowledge-sharing activities.
  • Collaborate with business and technical stakeholders to translate requirements into scalable data solutions.
  • Evaluate emerging technologies and contribute to the evolution of the enterprise analytics platform.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field.
  • 8+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related discipline.
  • Advanced SQL and Python and ideally dbt or similar tool
  • Extensive experience building and maintaining analytics data models and transformation frameworks.
  • Strong understanding of dimensional modeling, semantic modeling, and enterprise reporting architectures.
  • Experience working in modern cloud-based data platforms and lakehouse environments.
  • Expertise with software engineering best practices including Git, automated testing, CI/CD, and code reviews.
  • Experience supporting AI, machine learning, or advanced analytics initiatives through data engineering and modeling solutions.
  • Strong understanding of data governance, quality, privacy, and security principles.
  • Excellent communication skills and the ability to partner with both technical and non-technical stakeholders.

Preferred Qualifications

  • Experience with dbt or similar analytics engineering tools.
  • Experience with modern orchestration platforms.
  • Exposure to semantic layer technologies, metadata management, and metrics frameworks.
  • Experience supporting generative AI, LLM, RAG, or machine learning initiatives.
  • Experience serving as a technical lead on complex data platform projects.

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