Data & Analytics Engineer

Role Overview

The Data & Analytics Engineer is a hands-on practitioner responsible for developing data, analytics, business intelligence, and data science solutions that support institutional decision-making and operations. This role works across the analytics lifecycle, including data transformation, analytics-ready data structures, semantic modeling, business intelligence, advanced analytics, predictive modeling, and AI.

What You Will Do

Designs, develops, and maintains scalable data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies. Transforms raw and complex source data into well-structured, analytics-ready datasets to support institutional reporting, business intelligence, advanced analytics, and data science initiatives.

Why It Might Be a Fit

Ability to design, develop, and maintain data and analytics solutions using Microsoft Fabric, SQL, Python, and related technologies, applying sound data modeling, software engineering, version control, testing, documentation, and deployment practices.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Statistics, Mathematics, Engineering, or a related field.
• 3 to 5 years of experience in data analytics, analytics engineering, business intelligence, data science, data engineering, or a related field.
• Experience with Microsoft Power BI or comparable business intelligence and visualization technologies, developing analytical data models and transforming source data into analytics-ready datasets.
• Experience working with data warehouses, lakehouses, data pipelines, or modern cloud-based data platforms with software development practices such as source control, testing, documentation, and code review.
• Understanding of data visualization, dimensional modeling, business intelligence concepts, statistical analysis and data science concepts.
• Proficiency in Python or a comparable programming language used for data analysis, automation, or data science.
• Strong SQL skills and experience working with complex analytical datasets.
• Ability to translate business requirements and questions into data and analytical solutions.

Tagged as: Data Analysis, Data Visualization, Power BI, Python, SQL