Azure Lead Data Engineer
Why This Role Stands Out
Lead impactful data initiatives and elevate your skills by designing and optimizing enterprise-scale data pipelines using Azure, Snowflake, and DBT in this remote, hybrid role. If you're a seasoned data engineering leader eager to mentor teams and architect modern cloud solutions, this opportunity offers competitive compensation and a chance to drive best practices.
Quick Overview
Job Description
Job Title: Azure Lead Data Engineer (Azure LDE)
Location: Remote
Employment Type: Contract
Rate: $60/hr
Experience Required: 8+ Years
We are seeking an experienced Azure Lead Data Engineer with strong expertise in Azure Cloud, Snowflake, Azure Data Factory (ADF), and DBT to design, build, and optimize enterprise-scale data pipelines. This is an excellent opportunity for a hands-on data engineering leader who can architect modern cloud data solutions while mentoring engineering teams and driving best practices in data integration, governance, and performance optimization.
Top Required Skills:
Azure Cloud & Azure Data Factory (ADF)
Snowflake & SnowSQL
DBT (Data Build Tool)
Key Responsibilities:
Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
Build and optimize data integration workflows that ingest and transform data from multiple enterprise source systems into Snowflake.
Develop efficient, optimized SQL queries for data extraction, transformation, and validation.
Collaborate with business stakeholders to understand requirements and translate them into scalable technical solutions.
Monitor, troubleshoot, and optimize data pipelines to ensure high availability, reliability, and performance.
Provide technical leadership, mentoring, and guidance to junior Data Engineers.
Implement and maintain data quality, governance, metadata, and documentation standards.
Work closely with Data Architects, Data Analysts, DevOps, and cross-functional teams in a cloud-native environment.
Support continuous improvement initiatives for cloud data engineering and automation.
Required Qualifications:
Bachelor''s degree in Computer Science, Data Engineering, Information Technology, or a related field.
8+ years of experience in Data Engineering with Azure cloud technologies.
Strong hands-on experience with Azure Cloud Platform services.
Proven expertise in Azure Data Factory (ADF) for orchestration and automation of enterprise data pipelines.
Advanced SQL skills for complex data transformation and performance optimization.
Strong experience with Snowflake, SnowSQL, and cloud data warehousing.
Hands-on experience with DBT (Data Build Tool) for data modeling and warehouse transformations.
Experience working with large-scale cloud-based data platforms and enterprise datasets.
Excellent analytical, problem-solving, communication, and collaboration skills.
Preferred Qualifications:
Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse Analytics, or Azure Functions.
Experience with Python or PySpark for custom data processing and transformations.
Knowledge of CI/CD pipelines, DevOps practices, and deployment automation for data engineering.
Experience with data governance, metadata management, or enterprise data catalog tools.
Familiarity with Power BI, Tableau, or other business intelligence platforms.
If you are a seasoned Azure Data Engineer with expertise in Azure, Snowflake, DBT, and cloud-native data engineering, we''d love to hear from you. Apply today with your updated resume.
Skills
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