Role Overview
As a Senior Data Engineer, you will lead the design, development, and maintenance of scalable data pipelines. You will be responsible for automating data flows, transforming complex datasets, and optimizing our modern data stack to support global analytics and business intelligence initiatives.
Key Responsibilities
- Pipeline Engineering: Design and build robust ETL/ELT pipelines to automate data movement from various source systems to cloud environments.
- Data Transformation: Develop and maintain high-performance code for data processing and transformation.
- Platform Management: Utilize and optimize the Azure-based data ecosystem, ensuring data quality and system reliability.
- Strategy & Collaboration: Partner with cross-functional teams to translate business requirements into technical data solutions.
- System Optimization: Continuously monitor and improve the performance and scalability of the data warehouse and analytics platforms.
Technical Requirements
- Cloud Platform: Proven experience with Microsoft Azure.
- Data Warehousing: Deep expertise in Snowflake and Microsoft Fabric.
- Core Languages: Mastery of SQL and proficiency in Python or PySpark.
- Orchestration: Hands-on experience with Azure Data Factory (ADF).
- Data Modeling: Strong understanding of data architecture and modeling principles.
Qualifications
- Experience: Significant professional experience in Data Engineering, specifically within cloud-native environments.
- Technical Leadership: Ability to lead technical projects and mentor junior team members.
- Communication: Strong ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Proven track record of troubleshooting complex data issues and optimizing pipeline efficiency.
