Analytics Engineer - dbt/SQL/Python

Motion Recruitment Partners LLC.
Boston, MA, United States
26 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Working hours
Regular working hours
Job source

Tech stack

Training Data Artificial Intelligence Airflow Amazon Web Services Data Analysis Apache HTTP Server Application Integration Architecture Business Logic Cloud Database Software Quality Code Review Information Systems
+27 more
Continuous Integration Data Architecture Information Engineering Data Governance Data Transformation Graph Database Python (Programming Language) Machine Learning Meta-Data Management Operational Databases Software Construction SQL Databases Cloud Platform System Feature Engineering Sql Optimization Large Language Models Generative AI Agentic-AI Data Strategy Git Data Layers Containerization Kubernetes Information Technology Machine Learning Operations Software Version Control Data Pipelines

Job description

Working across analytics engineering, data engineering, architecture, and artificial intelligence, you will establish trusted, reusable data products and create the semantic foundation needed for AI agents, machine learning workflows, and business intelligence initiatives. This is a highly visible technical leadership role focused on solving complex data challenges, defining engineering standards, and shaping the future of data and AI platforms. You will collaborate closely with engineers, architects, analysts, researchers, and business stakeholders while serving as a technical mentor and subject matter expert on strategic initiatives. Required Skills & Experience, * Architect and develop scalable analytics-ready data models and enterprise data products

  • Design and implement modern lakehouse architectures using cloud-native technologies
  • Establish and govern semantic layers, business metrics, and enterprise business logic
  • Build AI-ready data interfaces and context frameworks that enable trusted analytics and AI applications
  • Design and optimize batch and event-driven data pipelines
  • Develop feature engineering, model scoring, and embedding pipelines to support analytics and machine learning initiatives
  • Establish engineering standards for testing, source control, CI/CD, documentation, and code quality
  • Implement data quality monitoring, lineage, observability, and governance frameworks
  • Lead technical planning and execution of cross-functional projects
  • Mentor engineers through architecture reviews, design guidance, and code reviews
  • Evaluate emerging technologies and contribute to the long-term analytics and AI data strategy

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Information Systems, Analytics, or a related field, or equivalent experience
  • 8+ years of experience in analytics engineering, data engineering, or a related technical discipline
  • Advanced SQL and Python development skills
  • Extensive experience with dbt or similar data transformation frameworks
  • Strong expertise in data modeling, data architecture, and semantic layer design
  • Experience building scalable cloud-based data platforms and lakehouse architectures
  • Hands-on experience with software engineering best practices including Git, testing, CI/CD, and code reviews
  • Experience designing and supporting production data pipelines and orchestration frameworks
  • Knowledge of data governance, privacy, security, and compliance practices
  • Proven ability to lead complex technical initiatives and collaborate across technical and non-technical teams
  • Excellent communication, mentorship, and stakeholder management skills

Desired Skills & Experience

  • Advanced degree in a related technical field
  • Experience with Apache Iceberg, Trino, AWS, or similar cloud data technologies
  • Knowledge of Dagster or other workflow orchestration platforms
  • Experience supporting AI and machine learning use cases through data engineering
  • Familiarity with large language models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, or text-to-SQL solutions
  • Exposure to semantic knowledge models, metadata management, or knowledge graph technologies
  • Familiarity with emerging AI integration standards and frameworks, Applicants must be currently authorized to work in the US on a full-time basis now and in the future.

Benefits & conditions

  • Competitive salary and comprehensive benefits package
  • Hybrid work environment
  • Opportunity to influence enterprise-wide data and AI strategy
  • Professional development and continuing education opportunities
  • Collaborative and mission-driven culture
  • Exposure to cutting-edge analytics, cloud, and AI technologies

You will receive the following benefits

  • Medical Insurance
  • Dental Benefits
  • Vision Benefits
  • Paid Time Off (PTO)
  • 401(k)

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