Data Analytics Engineer

Responsibilities

• Build & Optimize Pipelines: Design, implement, and maintain robust, high-performance ELT/ETL data pipelines within Microsoft Fabric and our broader data environment.
• Data Integration: Connect and harmonize new data sources—including ERP, e-commerce platforms, and external APIs—into a centralized data platform.
• Analytics Data Modeling: Transform raw data into clean, well-structured dimensional models, data marts, and reusable datasets (star schemas) that are analysis-ready for reporting and self-service BI.
• Semantic Layer & Metrics: Build and maintain semantic models and standardized metric definitions in Power BI and Microsoft Fabric so the business works from a single, trusted source of truth.
• Data Quality & Testing: Implement automated testing, validation, and monitoring to ensure pipelines and datasets are accurate, reliable, and well-documented.
• Collaboration: Partner with analysts and stakeholders across Sales, Marketing, Operations, and Product to translate business requirements into reliable data products.
• Continuous Improvement: Follow and help improve team standards for coding, documentation, version control, and DataOps across our data engineering and analytics workflows.

Qualifications

• 3+ years of hands-on experience as a Data Engineer, Analytics Engineer, or equivalent
• Experience building and maintaining production-grade data pipelines and analytics data models
• Proficiency in Python, PySpark, and SQL
• Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience)
• PREFERRED: Experience with Microsoft Fabric, Azure Synapse, or Azure Data Lake
• PREFERRED: Preferred experience implementing DataOps best practices and building transformation models with dbt or similar frameworks
• Familiarity with API integrations and third-party data ingestion
• Knowledge of data governance and data quality frameworks
• Musician or passion for music a plus