Job Title: Lead Azure Data Engineer
Location: Atlanta, GA (Hybrid)
Experience: 10+ Years
Employment Type: Long – Term Contract

Job Description:

We are seeking a highly experienced Lead Azure Data Engineer to join our team on a contract basis. This role is ideal for a data engineering professional with a deep understanding of Azure cloud technologies and modern data warehousing practices. The ideal candidate will have a strong background in Data Vault modeling, enterprise data architecture, and experience working with Microsoft Fabric, Databricks, or similar big data platforms.

Key Responsibilities:

Lead the design, development, and deployment of scalable data pipelines and ETL/ELT processes on Azure cloud platforms.
Architect and implement Data Vault 2.0 models and methodologies for enterprise data warehousing.
Collaborate with data architects, analysts, and business stakeholders to translate data requirements into technical solutions.
Optimize and manage data flows across various sources, using Azure Data Factory, Synapse Analytics, Databricks, and other Azure-native services.
Contribute to the evaluation and adoption of emerging tools and technologies, including Microsoft Fabric.
Provide technical leadership and mentorship to junior data engineers and team members.
Ensure best practices for data governance, data quality, and security are followed.

Must-Have Skills:

10+ years of experience in Data Engineering or related field.
Strong proficiency in Data Vault modeling techniques and data warehousing concepts.
Hands-on experience with Azure Cloud services (Data Factory, Synapse, Data Lake, etc.).
Working knowledge of Microsoft Fabric or willingness to learn and lead adoption.
Experience with Databricks, Apache Spark, or similar big data platforms.
Proficiency in SQL, Python, or Scala for data processing and transformation.
Strong problem-solving and communication skills.

Preferred Qualifications:

Azure Data Engineer Certification (e.g., DP-203) is a plus.
Experience with CI/CD pipelines and DevOps practices for data solutions.
Familiarity with data mesh or modern data architecture frameworks.