Analytics Engineer

About Intermedia

What You'll Do:

• Work directly with business stakeholders to understand their domain and translate questions into data solutions — delivering iteratively from quick explorations to production-ready data products
• Design and build data models (dimensional models, semantic layers) and implement them as Snowflake views, DBT marts, and Power BI datasets
• Build and optimize Power BI semantic models (DAX, Power Query) and design reports that surface your models effectively
• Write consumption-layer SQL (views, transforms, analytical queries) across Snowflake and SQL Server to serve downstream analytics
• Consolidate data solutions into modern analytics platforms, improving consistency and reducing technical debt
• Define and document metric definitions, business logic, and data product specifications
• Design and implement data quality tests (dbt tests, SQL validations) and contribute to the team's testing standards and governance framework
• Collaborate with Data Engineers through code reviews, shared planning, and PR-based workflows

What You Will Bring to the Role:

• Bachelor's degree in Computer Science, Data Analytics, Statistics, Mathematics, Economics, or related quantitative field
• 3–5 years of experience in analytics engineering, data analysis, BI engineering, or related roles
• Curiosity and drive to deeply understand the business domains you support
• Strong SQL skills: complex queries, window functions, CTEs, performance tuning across cloud data warehouses
• Experience with data modeling — dimensional models, semantic layers (Power BI datasets, SSAS tabular), or structured consumption models
• Proficiency in Power BI: report design, DAX, Power Query, and data model optimization
• Understanding of data visualization best practices — you care about how information is presented, not just that it renders
• Experience with Snowflake or a similar cloud data platform
• Experience working across multiple data sources and environments (data warehouses, operational databases, APIs)
• Familiarity with Git-based development workflows — branching, pull requests, code review, and working across dev/staging/prod environments
• Comfortable presenting to business stakeholders and explaining data concepts in plain language
• Comfortable working in agile sprints with iterative delivery

Even Better If You Have

• Experience using AI coding agents (GitHub Copilot, Codex, Claude Code, or similar) to accelerate development, analysis, or documentation
• Experience with DBT for data transformations
• Python for data analysis, scripting, or automation
• Experience with MicroStrategy reporting or administration
• Familiarity with data catalog or data governance tools
• Background in telecommunications, SaaS, or B2B industries