Location: Richmond, VA - Must live within 50 miles
Position Type: Hybrid - 3 days onsite
Contract Length: 2 months + extension Seeking a senior ETL developer to design, build, and optimize cloud-based data management and warehousing solutions by extracting, transforming, and loading business data. The role involves collaborating with cross-functional teams, utilizing tools like Azure Data Factory, Databricks, Python, and SQL, and applying advanced data architecture techniques.
Required Skills: - 10+ years designing and developing systems for data asset management, ETL processes, and business intelligence.
- 10+ years designing and supporting data warehouse schemas and developing data marts for new and existing data sources.
- 10+ years collaborating with data analysts, scientists, and business users to gather requirements and populate data hubs and warehouses.
- 10+ years of advanced understanding of data integrations, strong database architecture knowledge, and experience ingesting spatial data.
- 10+ years of experience resolving conflicts, prioritizing tasks, and managing multiple projects.
- 10+ years of proficiency with Microsoft Office tools: Word, PowerPoint, Excel, Project, Visio, and Team Foundation Server.
- 10+ years of experience with data warehousing architectures including Kimball and Inmon, and designing solutions across various data stores.
- 10+ years of hands-on experience with Azure technologies: Data Factory v2, Data Lake Store, Data Lake Analytics, Azure Analysis Services, Azure Synapse.
- 10+ years of experience with IBM Datastage, Erwin, SQL Server (SSIS, SSRS, SSAS), Oracle, T-SQL, Azure SQL Database, and Azure SQL Data Warehouse.
- 10+ years of experience in Windows and Unix environments with scripting in Python and/or Linux shell scripting.
- 10+ years of experience in Azure cloud engineering.
- Preferred: 5+ years of experience with Snowflake.
Duties: - Design and develop integrations for enterprise data assets, ETL processes, and business intelligence solutions.
- Build and maintain data engineering processes that leverage a cloud-based architecture, including migrating legacy pipelines as needed.
- Design and support data warehouse schemas and develop data marts for new and existing data sources.
- Collaborate with data analysts, scientists, and other stakeholders to gather requirements and populate optimized data warehouse structures.
- Partner with data modelers and architects to refine and implement business data requirements for building and maintaining enterprise data assets.