Data Analyst – Analytics Engineering & AI

Role Overview

The Data Analyst will work at the intersection of business analytics, data visualization, analytics engineering, data modeling, and AI-enabled analytics. The role will partner with business stakeholders, senior analysts, data engineers, architects, and product teams to transform business questions into trusted datasets, analytical models, dashboards, reports, and actionable insights.

What You Will Do

The Data Analyst will analyze large and complex datasets to identify trends, patterns, opportunities, anomalies, and drivers of business performance. The role will also develop recurring and ad hoc analyses supporting commercial, customer, digital, operational, and strategic initiatives.

Why It Might Be a Fit

The ideal candidate is analytically curious, technically capable, comfortable working with complex data, and interested in developing skills across analytics engineering, semantic modeling, and AI-enabled analytics.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, Business Analytics, Statistics, Mathematics, Economics, or a related quantitative discipline.
• 2–5 years of experience in data analytics, business intelligence, analytics engineering, data engineering, data science, or a related discipline.
• Strong SQL skills, including joins, aggregations, subqueries, common table expressions, window functions, and analytical querying.
• Working knowledge of Python or another analytical programming language for data manipulation, automation, analysis, or validation.
• Experience with visualization and business intelligence technologies such as Tableau, Power BI, or similar tools.
• Understanding of data structures, relational databases, analytical datasets, and basic data modeling concepts.
• Familiarity with ETL/ELT concepts and modern data-transformation workflows.
• Understanding of data-quality principles, including validation, reconciliation, completeness, consistency, and accuracy.
• Basic understanding of cloud data architectures and modern data warehouse technologies.
• Interest in or exposure to generative AI, large language models, semantic search, embeddings, knowledge models, or AI agents is preferred.

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• Paid time off
• Retirement plan
• Learning budget
• Parental leave
• Wellness programs
• Visa sponsorship available
• Relocation assistance

Tagged as: Data Analysis