Data Engineer

• Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization.
• Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements.
• Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources.
• Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform.
• Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput.
• Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data.
• Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs.
• Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing.
• Training: You'll train and collaborate with teammates effectively in data engineering best practices
• Technical Influence/Leadership: Recommends policy changes and establishes department-wide procedures. Uses extensive experience and knowledge to resolve complex problems.
• Monitor and manage production environment to deliver data within defined SLAs

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