Data Engineer

• Build, maintain, and optimize scalable data pipelines and data processing workflows.
• Connect and integrate data from multiple enterprise source systems.
• Develop ETL/ELT processes and data transformations.
• Work with structured and unstructured data sources.
• Implement data quality checks, validation, monitoring, and remediation processes.
• Develop reusable and scalable data pipelines.
• Troubleshoot pipeline failures and data-related issues.
• Ensure data is accurate, consistent, accessible, and reliable.
• Collaborate with Application Developers, Data Scientists, Business Analysts, and Solution Architects.
• Optimize data pipelines for performance, reliability, and scalability.
• Document data flows, transformations, dependencies, and technical processes.
• Support data testing, deployment, and ongoing maintenance.

Requirements

• 3+ years of experience in Data Engineering, ETL/ELT, or a related technical field.
• Strong SQL and Python skills.
• Experience building data pipelines and integrating multiple source systems.
• Experience with databases, data warehouses, APIs, and cloud technologies.
• Strong understanding of data quality, validation, governance, and data lineage.
• Experience working with large and complex datasets.
• Strong troubleshooting and problem-solving skills.
• Experience working in Agile or cross-functional technical environments.

Preferred Technical Skills

• Python
• SQL
• ETL/ELT
• Data pipelines
• APIs
• Data integration
• Cloud platforms
• Data warehouses
• Databases
• Data quality and governance