Data Warehouse Engineer

ParsonsKellogg is a company focused on critical infrastructure solutions, and they are seeking a Data Warehouse Engineer to design, develop, and maintain scalable data warehouse solutions. This role involves building efficient data pipelines and integrating data from various sources to support analytics and reporting needs.

Responsibilities:

• Design, develop, and maintain enterprise data warehouse solutions using modern data warehousing principles
• Build and manage ETL/ELT pipelines to ingest and transform data from various structured and unstructured sources
• Develop and maintain dimensional data models optimized for analytics and reporting
• Write efficient, scalable SQL queries and optimize database performance
• Integrate data from systems such as relational databases, cloud platforms, APIs, SharePoint, flat files, and enterprise applications
• Support data preparation and modeling needs for analytics platforms such as Power BI
• Implement data validation, monitoring, and quality control processes to ensure data integrity
• Collaborate with analytics and application development teams to support reporting and application requirements
• Support cloud-based data platform development, primarily within the Microsoft Azure ecosystem
• Work with both traditional ETL tools and modern cloud-based data integration tools
• Document data models, pipeline processes, and system architecture
• Design and implement data warehouse schemas, including fact and dimension tables
• Develop ETL/ELT pipelines using Azure Data Factory, SSIS, Microsoft Fabric, or similar tools
• Build and maintain Azure SQL databases, data lakes, Synapse, or Fabric-based warehouse environments
• Transform and integrate data from multiple enterprise systems into centralized warehouse environments
• Work with structured and semi-structured data formats, including Parquet files, CSV, and JSON
• Optimize data structures and queries to improve performance and scalability
• Support Power BI development teams by providing clean, structured, and performant data models
• Assist in the design and implementation of cloud-based data platform architecture
• Support backend data integration for Power Platform solutions, including Power BI and Power Pages
• Troubleshoot and resolve data pipeline, performance, and integration issues
• Assist in establishing and maintaining data engineering and data warehousing best practices

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Analytics, or related technical field (or equivalent work experience)
• 3–7+ years of experience in data engineering, data warehousing, or related field
• Strong proficiency in SQL, including query optimization, indexing, and performance tuning
• Experience designing and implementing data warehouse architectures and dimensional data models
• Experience developing ETL/ELT pipelines and data integration workflows
• Experience with SQL Server Integration Services (SSIS)
• Experience working with relational databases such as SQL Server, Azure SQL, or similar platforms
• Experience working with structured and semi-structured data formats, including Parquet files
• Experience working within Microsoft Azure data ecosystem, including tools such as: Azure Data Factory, Azure SQL Database, Azure Synapse Analytics, Microsoft Fabric, Azure Data Lake Storage
• Experience supporting Power BI semantic models and analytics environments
• Experience working with data lake architectures and modern cloud data platforms
• Experience with scripting languages such as Python for data processing and automation
• Experience supporting Power Platform solutions, including Power BI and Power Pages
• Experience working in consulting or project-based environments