Lead Data Engineer – Azure & Snowflake

Location: Ohio (Preferred) / Remote Employment Type: Contract / Full-Time Experience: 10+ Years Position Overview We are seeking an experienced Lead Data Engineer – Azure & Snowflake to design, develop, and optimize enterprise‑scale data platforms and cloud‑native data solutions. The ideal candidate will have deep expertise in Azure Data Factory (ADF), Snowflake, DBT, and SQL , with a strong background in building scalable ETL/ELT pipelines and modern data architectures. This role requires technical leadership, hands‑on development, and collaboration with cross‑functional teams to deliver high‑quality, data‑driven solutions that support analytics and business intelligence initiatives. Key Responsibilities Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory (ADF), Snowflake, and DBT . Build and manage data integration workflows from multiple source systems into Snowflake. Develop efficient and optimized SQL queries for data extraction, transformation, and loading processes. Collaborate with business stakeholders to gather requirements and translate them into scalable technical solutions. Monitor, troubleshoot, and optimize data pipelines to ensure performance, reliability, and scalability. Provide technical leadership, mentorship, and best practices guidance to junior data engineers. Implement and maintain data quality, governance, and documentation standards. Work closely with Data Architects, Analysts, and DevOps teams in a cloud‑native environment. Support production deployments, issue resolution, and continuous process improvements. Required Qualifications Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field. 8+ years of experience in Data Engineering, Data Warehousing, or Cloud Data Platforms. Strong hands‑on experience with: Microsoft Azure Cloud Platform Azure Data Factory (ADF) Snowflake SnowSQL DBT (Data Build Tool) SQL and Data Modeling Experience building and supporting large‑scale cloud‑based data environments. Strong understanding of data integration, data warehousing, and ELT/ETL best practices. Excellent analytical, problem‑solving, and communication skills. Preferred Qualifications Experience with Python or PySpark for custom transformations and automation. Knowledge of CI/CD pipelines and DevOps practices for data engineering. Exposure to: Data Governance Metadata Management Data Catalog tools Familiarity with BI and reporting tools such as: Power BI Tableau Technical Skills Azure Data Factory (ADF) Snowflake & SnowSQL DBT (Data Build Tool) SQL Performance Tuning Data Warehousing ETL/ELT Development Azure Cloud Services Data Modeling Python / PySpark (Preferred) Azure Synapse Azure Data Lake CI/CD & DevOps #J-18808-Ljbffr