Integrity is seeking an Associate Data Engineer Manager to lead and support the development of large-scale, complex data implementations within the insurance industry, aiming to build, enhance, and maintain a scalable data ecosystem.
Requirements
- advanced SQL, including query optimization and stored procedure development.
- enterprise data warehousing, data modeling, and analytics best practices.
- leading data engineering team with 5+ years of experience in technical project management within the EDW/BI space.
- Master Data Management (MDM) and Snowflake
- Microsoft Azure services, including Azure Data Factory (ADF), and Logic Apps
- ETL tools such as Talend, Nexla, Stitch, or Mito.
- data orchestration and scheduling tools such as Apache Airflow.
Responsibilities
- Lead the analysis, design, and implementation of data solutions within the Enterprise Data Warehouse (EDW).
- Design, build, and maintain ETL pipelines using Azure Data Factory, Logic Apps, and other modern data tools.
- Conduct Data mapping, Data Collection, Data profiling and Data storage plans to support project/product needs.
- Write efficient T-SQL, DDL/DML scripts, and develop stored procedures, functions, and complex Snowflake procedures.
- Manage the development and maintenance of robust Snowflake and SQL scripts for data extraction and transformation.
- Ensure high-quality, scalable data integration solutions across platforms and business functions.
- Define and execute test strategies, scenarios, and test data for all development deliverables.
Other
- Lead and support the development of large-scale, complex data implementations.
- Collaborate closely with the Data Engineering teams to build, enhance, and maintain a scalable data ecosystem.
- Experience managing distributed teams (onsite, remote, and international), and a commitment to continuous improvement and innovation.
- Collaborate with business and technical stakeholders to gather requirements and prepare technical documentation.
- Partner with business users to optimize processes, improve existing systems, and troubleshoot data and integration issues.
