Senior Data Engineer (Machine Learning Enablement)

About the role

Build scalable, cloud-native data platforms.

Tasks

• Design, develop, and optimize ETL/ELT pipelines using Azure Data Factory, Azure Databricks, Azure Functions, and Synapse Analytics.
• Integrate external retailer and third-party datasets into Bronze, Silver, and Gold medallion architecture layers.
• Profile datasets, resolve data quality issues, and manage missing, duplicate, or unmatched records.
• Implement dimensional modeling, master data alignment, and reliable join strategies.
• Execute large-scale, multi-terabyte data migrations with minimal downtime.
• Transform complex semi-structured data, including XML, into analysis-ready formats.
• Establish data governance, validation, quality controls, and feature-ready data models.
• Collaborate with Data Science and ML teams to productionize machine learning models.
• Maintain code quality, version control, documentation, and code reviews using GitHub.

Requirements

• 7+ years of experience in data engineering, platform development, or data architecture.
• Strong hands-on experience with Azure Data Factory, Azure Databricks, Azure Functions, and Synapse Analytics.
• Expertise in Python, SQL, PySpark, or pandas.
• Experience with medallion architecture, dimensional modeling, and master data integration.
• Strong understanding of data governance, data quality, ETL/ELT pipelines, and large-scale data processing.
• Preferred: Exposure to AWS or GCP.
• Preferred: Salesforce integrations, APIs, data synchronization, or migrations.
• Preferred: Retail or con

Schedule

• 6–12 Months Contract
• Occasional onsite visits to Midtown Atlanta

Location

• Atlanta, GA (Occasional onsite visits to Midtown Atlanta)