Senior Azure Data Engineer

• Design, develop, and maintain data ingestion, transformation, and integration pipelines using Azure Data Factory, Microsoft Fabric, and Azure Synapse Analytics.

• Design, develop, and maintain data ingestion, transformation, and integration pipelines using Azure Data Factory, Microsoft Fabric, and Azure Synapse Analytics.
• Integrate data from disparate systems and applications, ensuring data is reliable, well-documented, and fit for downstream analytics.
• Develop and maintain scalable data-processing solutions using Python and PySpark.
• Write, review, and optimize SQL programs for data transformation, analysis, and reporting, including complex queries and database objects as appropriate.
• Optimize data flows and pipeline performance for scalability, efficiency, and reliability.

• Architect and implement Azure Data Lake and Delta Lake solutions for structured and unstructured data.

• Architect and implement Azure Data Lake and Delta Lake solutions for structured and unstructured data.
• Build and support data solutions using Microsoft Fabric and its applicable data engineering and analytics capabilities.
• Utilize cloud-based data warehouse and data lake solutions.
• Apply modern data architecture patterns, including Medallion (Bronze/Silver/Gold) design.

• Partner with finance and business stakeholders to understand financial planning, forecasting, and analytical requirements and translate them into data solutions.

• Partner with finance and business stakeholders to understand financial planning, forecasting, and analytical requirements and translate them into data solutions.
• Work with financial models and the data that supports them, helping ensure inputs, transformations, assumptions, and outputs are traceable and reliable.
• Prepare, integrate, validate, and structure financial and operational data for modeling, analysis, and business intelligence.
• Collaborate with analysts to improve the quality, consistency, and usability of data used in financial and performance reporting.

• Provide technical guidance and promote engineering best practices for Azure- and Fabric-based data solutions.

• Provide technical guidance and promote engineering best practices for Azure- and Fabric-based data solutions.
• Communicate technical concepts, design decisions, and data limitations clearly to technical and non-technical audiences.

• Strong understanding of data modeling, including dimensional modeling, star schemas, and snowflake schemas.

• Strong understanding of data modeling, including dimensional modeling, star schemas, and snowflake schemas.
• Hands-on experience with Azure Data Lake Storage Gen2, Azure Data Factory, Azure SQL Database, and Azure Synapse Analytics or SQL Data Warehouse.
• Hands-on experience with Microsoft Fabric for data engineering, data integration, or analytics workloads.
• Strong experience programming in SQL, including writing and tuning complex queries and working with relational database objects.
• Proficiency in Python and PySpark for data processing and transformation.
• Demonstrated experience working with financial models or financial modeling processes, and preparing or validating financial data for forecasting, planning, or analytical use.
• Familiarity with Power BI or other data visualization tools.
• Knowledge of modern data architectures, including Medallion (Bronze/Silver/Gold) design patterns.

• Excellent communication and collaboration skills, with the ability to work effectively across technical and business teams.

• Excellent communication and collaboration skills, with the ability to work effectively across technical and business teams.
• Strong analytical, troubleshooting, and problem-solving abilities.
• Ability to manage priorities and deliver in a dynamic, fast-paced environment.
• Strong documentation and reporting skills.

• 8+ years of experience in data engineering, with a focus on cloud-based architecture.

• 8+ years of experience in data engineering, with a focus on cloud-based architecture.
• Proven expertise in the Azure data ecosystem and experience delivering production data solutions.
• Demonstrated hands-on experience with Microsoft Fabric, PySpark, and SQL programming.
• Experience working with financial models or financial modeling data and requirements.
• Bachelor’s degree in mathematics, Statistics, Economics, Engineering, or a related business or analytical discipline.
• Domain experience in supply chain management, logistics, or finance analytics, supporting data-driven decision-making across the enterprise.