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.
