Senior Data Engineer
Our client, a Financial Services company, is looking for a proactive, solutions focused Senior Data Engineer to join their team. Here, you will create semantic models for the consolidated data storage, use published data sets in Power BI, dataflows, and sourced data on SQL databases, with the goal of modernizing legacy SQL databases into Fabric Architecture. Must currently live in Austin, Texas to be considered. Competitive pay and benefits are all compensation facets.
Top Technical Requirements:
• 8 years of experience in business intelligence development, data engineering, or cloud data architecture
• Proficiency in PySpark for data processing and transformation.
• Strong experience with Azure Data Factory and Azure Data Pipelines.
• Expertise with Microsoft Fabric for end-to-end modelling
• Experience in Power BI data modeling (DAX, Power Query, dataset optimization)
• Extensive experience in creating and configuring data lakes, SQL Server databases, and data warehouses in Azure.
Legacy tech stack: SSIS / SSAS / SSRS.
Nice To Haves:
• Certification in Azure Data Engineering or DP-600
• Previous experience modeling data so AI chatbot can consume it
• Expertise in data orchestration and automation.
• Familiar with Power App and Power Platform
Key Responsibilities:
• Design, develop, and maintain data pipelines using Azure Data Factory and Azure Data Pipelines.
• Implement data orchestration solutions to automate data workflows.
• Utilize PySpark for data processing and transformation tasks.
• Develop and automate ETL/ELT pipelines to transform raw data into structured, actionable insights, leveraging Microsoft Fabric and Power BI for efficient storage, processing, and reporting.
• Define and implement data governance frameworks, including data lineage, cataloging, standardization, and role-based access control (RBAC) to ensure enterprise-wide data accessibility and security
• Create and configure data lakes, SQL Server databases, and data warehouses in Azure.
• Ensure data quality, security, and compliance with industry standards.
• Troubleshoot and resolve data-related issues.
Our client, a Financial Services company, is looking for a proactive, solutions focused Senior Data Engineer to join their team. Here, you will create semantic models for the consolidated data storage, use published data sets in Power BI, dataflows, and sourced data on SQL databases, with the goal of modernizing legacy SQL databases into Fabric Architecture. Must currently live in Austin, Texas to be considered. Competitive pay and benefits are all compensation facets.
Top Technical Requirements:
• 8 years of experience in business intelligence development, data engineering, or cloud data architecture
• Proficiency in PySpark for data processing and transformation.
• Strong experience with Azure Data Factory and Azure Data Pipelines.
• Expertise with Microsoft Fabric for end-to-end modelling
• Experience in Power BI data modeling (DAX, Power Query, dataset optimization)
• Extensive experience in creating and configuring data lakes, SQL Server databases, and data warehouses in Azure.
Legacy tech stack: SSIS / SSAS / SSRS.
Nice To Haves:
• Certification in Azure Data Engineering or DP-600
• Previous experience modeling data so AI chatbot can consume it
• Expertise in data orchestration and automation.
• Familiar with Power App and Power Platform
Key Responsibilities:
• Design, develop, and maintain data pipelines using Azure Data Factory and Azure Data Pipelines.
• Implement data orchestration solutions to automate data workflows.
• Utilize PySpark for data processing and transformation tasks.
• Develop and automate ETL/ELT pipelines to transform raw data into structured, actionable insights, leveraging Microsoft Fabric and Power BI for efficient storage, processing, and reporting.
• Define and implement data governance frameworks, including data lineage, cataloging, standardization, and role-based access control (RBAC) to ensure enterprise-wide data accessibility and security
• Create and configure data lakes, SQL Server databases, and data warehouses in Azure.
• Ensure data quality, security, and compliance with industry standards.
• Troubleshoot and resolve data-related issues.
