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About the Role

The Business Intelligence team is seeking a Data Analytics Engineer to build, transform, and optimize the company's global data infrastructure. This role involves designing and maintaining data pipelines and modeling clean, well-tested datasets to support reporting and analytics. The ideal candidate is passionate about organizing data, solving complex data challenges, and enabling organizational data intelligence.

Responsibilities

Design, implement, and maintain robust, high-performance ELT/ETL data pipelines within Microsoft Fabric and the broader data environment.
Connect and harmonize new data sources, including ERP, e-commerce platforms, and external APIs, into a centralized data platform.
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.
Build and maintain semantic models and standardized metric definitions in Power BI and Microsoft Fabric.
Implement automated testing, validation, and monitoring to ensure pipelines and datasets are accurate, reliable, and well-documented.
Partner with analysts and stakeholders across Sales, Marketing, Operations, and Product to translate business requirements into reliable data products.
Follow and help improve team standards for coding, documentation, version control, and DataOps across data engineering and analytics workflows.

Requirements

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 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.
Strong programming in Python and PySpark for data processing and transformation.
Advanced SQL and dimensional data modeling (e.g., star schema / Kimball) for analytical performance and scalability.
Experience building and maintaining ELT/ETL pipelines and transformation layers, including automated testing and validation of analysis-ready datasets.
Strong understanding of cloud data platforms (Azure preferred).
Excellent communication skills with the ability to simplify complex technical concepts.
Familiarity with semantic modeling and BI tools such as Power BI and Microsoft Fabric.
Self-directed, highly organized, and comfortable operating in a fast-paced, evolving environment.
Passion for innovation and leveraging data to create business impact.

Skills

Python
PySpark
SQL
Microsoft Fabric
Azure Synapse
Azure Data Lake
dbt
API integrations
Data governance
Data quality frameworks
Dimensional data modeling
Star schema
Kimball methodology
ELT/ETL pipelines
Automated testing
Data validation
Cloud data platforms
Power BI
Semantic modeling

Location

US based

Work Type

Hybrid

Experience Level

3+ years

Education Level

Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience)

About the Company

D’Addario & Company is the largest manufacturer and distributor of musical instrument accessories in the world.
A US based manufacturing company that prides itself on high automation machinery, innovative technology, and environmentally sustainable practices.
Committed to making music education accessible worldwide through the D'Addario Foundation.
Values curiosity, passion, candor, family, and responsibility.