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.
Financial and Business Analytics
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.
Collaboration and Leadership
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.
Performance Monitoring and Optimization
Monitor data quality and performance metrics; investigate and resolve data-related issues.
Continuously optimize pipelines, SQL queries, and database structures for efficiency and reliability.
Apply appropriate data quality checks and operational controls to support trusted analytics.
Required Skills and Experience
Technical Skills
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.
Professional Skills
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.
Preferred Qualifications
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.
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