Lead Azure Data Engineer

Job Title: Lead Azure Data Engineer
Location:
Atlanta, GA (Hybrid)

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.