Data Engineer
Summary
Data engineer designing scalable data architectures and building ETL pipelines on Microsoft Azure (Fabric, Data Factory, Data Lake, SQL Data Warehouse), handling integration, storage optimization, security, and monitoring using SQL/Python and DevOps. Requires 3+ years of IT/data engineering experience; SAP Datasphere and AI-assisted tasks preferred.
Designing Data Solutions: Creating scalable and efficient data architectures using Fabric and/or Azure tools.
Building and Maintaining Data Pipelines: Developing ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes using tools like Azure Data Factory.
Data Integration: Ensuring seamless integration of data from different sources and maintaining data quality and consistency.
Data Storage Management: Managing and optimizing data storage solutions to ensure performance, scalability, and cost-effectiveness.
Ensuring Data Security and Compliance: Implementing data security measures and ensuring compliance with relevant data protection regulations.
Monitoring and Troubleshooting: Continuously monitoring data systems for performance issues and troubleshooting any problems that arise.
Basic QualificationsBachelor’s degree or foreign equivalent in Computer Science or related field.
3+ years of IT experience, including data engineering and Azure cloud solutions.
Proven experience implementing Azure Cloud services for data movement and transformations.
Mandatory Skills3+ years of hands‑on experience in design, support, development and delivery of data management, modeling, and analytics solutions. This includes hands‑on experience with data integration, ETL processes, and data modeling.
2+ years of Azure Data Lake and SQL Data Warehouse experience.
2+ years of Azure Data Factory and DevOps.
Proficiency in SQL or Python, or other programming languages used for data processing.
Ability to rapidly develop outcomes via specifications and requirements to build proof of concepts.
Profiling various information systems, capture source/target mappings and transformations based on project requirements.
Ability to rapidly define requirements and build proof of concepts.
Preferred Skills2+ years of SAP Datasphere / BDC.
1+ years utilizing AI to expedite data engineering tasks.
Other RequirementsAbility to work under tight timelines and manage complex requirements.
Flexible to work during CST/EST time zones and meet for hand-over activities to India team if needed.
Self-motivated, proactive, and a strong team player.