Data Engineer

Overview Client•Memphis, TN

About The Position

Client is seeking a Data Engineer to develop, maintain, test, and debug software and data integration solutions in both traditional and cloud-based environments. This role focuses on building and supporting scalable applications, data pipelines, and modern data platform solutions using technologies such as Azure Data Factory, Snowflake, Oracle, Microsoft SQL, .NET, and related tools. The position involves designing and maintaining ETL/ELT processes, defining system requirements through research and analysis, preparing detailed technical specifications, and ensuring reliable, high-quality data integration solutions that support business needs.

Requirements

Experience with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS) for cloud-based data pipelines and storage.
Strong knowledge of Snowflake architecture, including streams, tasks, and pipeline processing.
Experience with data ingestion tools such as Fivetran and HVR, and data transformation using dbtLabs.
Understanding of batch and near real-time data integration patterns.
Ability to design, implement, and support scalable cloud data architecture.
Experience with Git, CI/CD practices, and Azure DevOps in data engineering environments.
Experience documenting ETL designs, data mappings, and technical architecture.
Knowledge of data integrity, governance, lineage, production monitoring, and performance tuning.
Experience working with technologies such as PL/SQL, Oracle, Microsoft SQL, .NET, Azure Data Factory, Snowflake, and related data platform tools.

Responsibilities

Develop, maintain, test, debug, document, and support software applications and data integration solutions across traditional and cloud environments.
Design, build, and optimize scalable ETL/ELT pipelines and data processing solutions using modern cloud data platforms.
Formulate and define system scope, objectives, and technical requirements through research, analysis, and fact-finding.
Prepare detailed specifications, data mappings, and technical documentation for application and data integration development.
Develop and support cloud-based data pipelines and storage solutions utilizing Azure Data Factory and Azure Data Lake Storage.
Design, implement, and maintain Snowflake-based data solutions, including streams, tasks, and pipeline processing.
Monitor, troubleshoot, tune, and support production data environments to ensure performance, reliability, and data integrity.
Collaborate within development and data engineering workflows using Git, CI/CD processes, and Azure DevOps.