Job Description:
Position Summary
We are seeking a Senior Azure Data Engineer with 8+ years of experience designing, developing, and optimizing large-scale data platforms. The ideal candidate brings strong expertise in Microsoft Azure data services, Microsoft Fabric, and Data Lake architecture, along with hands-on experience in financial forecasting modeling, PySpark, and SQL programming.
In this role, you will collaborate with cross-functional teams to build robust, scalable, and secure data pipelines and analytics platforms that support business intelligence, financial planning and analysis, data science, and advanced analytics initiatives.
Key Responsibilities
Data Integration and Pipeline Development
- 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.
Cloud Architecture and Implementation
- 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.
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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