Senior Azure Data Engineer

Overview

Senior Azure Data Engineer role designing, developing and optimizing large-scale data platforms built on Microsoft Azure data services, Microsoft Fabric and Data Lake architecture, supporting business intelligence, financial planning and analysis, data science and advanced analytics.

What you'll do

• 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.
• 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.
• 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.
• Communicate technical concepts, design decisions and data limitations clearly to technical and non-technical audiences.
• 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.

What you'll need

• 8+ years of experience in data engineering, with a focus on cloud-based architecture.
• 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.
• Strong analytical, troubleshooting and problem-solving abilities.
• Ability to manage priorities and deliver in a dynamic, fast-paced environment.
• Strong documentation and reporting skills.

Nice to have

• 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.

Details

• Location: Hyderabad, Telangana, India.