Senior Analytics Engineer (Hybrid) - Data & AI Pipelines

Talentify; Boston (MA); Hybrid; USD 102,000 - 138,000; Full time

Benefits offered by this job

Medical, Vision, and Dental Insurance

401k Retirement Fund

Time Off: 13 holidays

Tuition Assistance Program

Job summary

Talentify seeks an Analytics Engineer III to design, develop, and maintain analytics-ready data models, semantic layers, and data pipelines powering reporting and AI-enabled workflows.

The role blends analytics engineering and data engineering, applying software practices to transform raw data into governed, reusable data products and to support AI analytics, agents, and ML workflows. Hybrid work in Boston with collaboration across university partners.

Qualifications

• 5+ years of analytics engineering, data engineering, BI development, or related field.
• Strong SQL and Python skills; experience building data models and transformations with dbt or similar tools.
• Experience with data modeling, data architecture, and semantic layer implementation in cloud lakehouse environments (S3, Iceberg, Trino).
• Ability to analyze technical requirements and deliver complex solutions with minimal oversight.
• Strong communication and understanding of data governance, privacy, and security practices.

Responsibilities

• Design, build, test, and maintain analytics-ready data models for reporting, analytics, and AI.
• Develop modular data models and transformations using dbt, SQL, and Python.
• Optimize models for performance, cost, and usability; support troubleshooting of data assets.
• Build semantic layers and metadata to ensure consistent definitions across tools and AI applications.
• Develop data pipelines using Dagster and AWS services; monitor operational health.

Skills

Advanced SQL

Python

dbt

Git

CI/CD

Data modeling

Data governance

Education

Bachelor's degree in Computer Science or related field

Tools

Dagster

AWS

Trino

Apache Iceberg

S3

Job description

Talentify seeks an Analytics Engineer III to design, develop, and maintain analytics-ready data models, semantic layers, and data pipelines powering reporting and AI-enabled workflows.

The role blends analytics engineering and data engineering, applying software practices to transform raw data into governed, reusable data products and to support AI analytics, agents, and ML workflows. Hybrid work in Boston with collaboration across university partners.