Senior Analytics Engineer

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Architect and oversee the development of scalable analytics data models and modern lakehouse data layers utilizing dbt, SQL, and Python.

• Design, develop, and sustain enterprise data models and transformation pipelines tailored for reporting, analytics, and AI applications.

• Establish and manage semantic layers, enterprise metrics, business logic, and metadata governance.

• Create AI-ready data architectures and interfaces that enable LLMs and AI agents to interpret and query institutional data.

• Spearhead context engineering projects involving semantic models, metadata, MCP, and text-to-SQL functionalities.

• Design and execute production-grade data and ML pipelines, encompassing feature engineering and embedding pipelines.

• Leverage Dagster and AWS to orchestrate, deploy, and oversee scalable data workflows.

• Set and enforce data engineering standards, data quality practices, automated testing, and best practices in software development.

• Conduct in-depth code reviews to ensure that analytics solutions are reliable, scalable, and maintainable.

• Drive technical planning and execution of cross-functional data and AI projects.

• Collaborate with data engineers, AI engineers, researchers, faculty, and business stakeholders.

• Mentor engineers and provide technical direction.

• Contribute to the long-term strategies for analytics engineering, data architecture, and AI.

⛳️ Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Science, Data Analytics, or a related technical discipline, or equivalent professional experience.

• 8+ years of professional experience in Analytics Engineering, Data Engineering, or a similar technical field.

• Proven experience leading complex data engineering or analytics engineering projects.

• Expert-level skills in SQL and Python programming.

• Extensive experience in constructing data models, transformations, and analytics workflows using dbt or comparable technologies.

• Strong understanding of data architecture, dimensional modeling, data warehousing, and semantic layer design.

• Experience with contemporary cloud data platforms and lakehouse architectures.

• Solid knowledge of Git, automated testing, CI/CD, code reviews, and data pipeline orchestration.

• Experience in designing and maintaining production-grade data pipelines.

• Familiarity with data governance, data quality, metadata management, privacy, and security.

• Exceptional communication and collaboration skills, with the capability to work effectively with both technical and non-technical stakeholders.

• Demonstrated experience mentoring engineers and providing technical leadership.

• Preferred: experience with AWS cloud services, particularly Amazon S3.

• Preferred: hands-on experience with Apache Iceberg and Trino.

• Preferred: experience with dbt Core or dbt Cloud.

• Preferred: experience with Dagster or similar orchestration tools.

• Preferred: experience in designing and implementing semantic layers and enterprise metrics frameworks.

• Preferred: experience supporting AI/ML initiatives involving LLMs, RAG, embeddings and vector-based search, text-to-SQL applications, AI agents, AI-ready data interfaces, and MCP.

• Preferred: experience in feature engineering and machine learning pipelines.

• Preferred: advanced degree in Computer Science, Data Science, Analytics, or a related field.

• Preferred: experience working with large institutional, research, or enterprise datasets.

🏝️ Benefits

• 9-month contract opportunity.

• Remote work arrangement.