Analytics Engineer (Full-time Hybrid)

Role Overview

The Analytics Engineer serves as a critical technical bridge between Data Engineering and Data Analytics, applying rigorous data engineering principles to the analytics development lifecycle.

What You Will Do

Design, build, and manage scalable analytics pipelines, develop and maintain complex Directed Acyclic Graphs (DAGs), and perform advanced extract, load and transform processes.

Why It Might Be a Fit

This role requires expertise in designing, building, and managing scalable analytics pipelines, semantic modeling, and leveraging Databricks and SQL Server to process large-scale datasets.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering or related field
• At least three (3) years designing and operating data analytics pipelines
• Designing, building, and managing scalable analytics pipelines in a modern data stack
• Expertise in developing and maintaining complex Directed Acyclic Graphs (DAGs)
• Semantic Modeling: Expertise in architecting and managing high-value semantic layers, metrics stores, and analytical cubes
• Proficiency in leveraging Databricks and SQL Server to process large-scale datasets
• Proficiency in managing PostgreSQL and SQL Server environments
• Ability to utilize AI-driven tools like GitHub Copilot
• Proficiency in applying software engineering principles
• Ability to translate complex business metrics and KPIs into technical artifacts
• Advanced technical skills in SQL and Python

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Life insurance
• Long Term Disability insurance
• Generous retirement savings plan
• Flexible work schedules including hybrid/remote options
• Paid time off including vacation, sick leave, holiday, management leave
• Dress flexibility

Tagged as: Data Analysis, Pipeline Management, Python, SQL