Data Engineer

About the Role A growing organization within the tech/innovation sector is seeking a Data Engineer to build scalable data pipelines, architect cloud-based solutions, and develop machine learning models that support enterprise decision-making. This role spans data engineering, model development, orchestration, and operationalization within a modern Azure + Fabric environment. Responsibilities Build and maintain enterprise-grade ETL/ELT pipelines using Azure Data Factory and Fabric Data Factory.

Develop and optimize data workflows leveraging Microsoft Fabric components (OneLake, Lakehouse, Warehouse). Train, deploy, and monitor machine learning models using notebooks, MLflow, and modern MLOps practices. Perform feature engineering using Python, SQL, and PySpark for model enhancement.

Implement CI/CD patterns for data science and model deployment. Conduct data quality checks, validation, and data integrity monitoring. Perform exploratory data analysis and communicate insights to cross-functional stakeholders.

Apply data architecture best practices such as Medallion Architecture and star-schema design. Create and maintain documentation for pipelines, models, and orchestration processes. Must-Have Qualifications Bachelor’s degree in Computer Science or related field (or equivalent experience). 3+ years of experience as a Data Science Engineer or in a similar hybrid data engineering/data science role.

Hands-on experience with Azure Data Stack (ADLS Gen2, Azure SQL, Key Vault). Strong proficiency in SQL, Python, and PySpark. Experience building data pipelines and developing ML models end‑to‑end.

Familiarity with Microsoft Fabric, data lake/lakehouse architectures, and MLOps (Azure DevOps or GitHub Actions). #J-18808-Ljbffr