About the job
- Take charge of the development of intricate data pipelines while enhancing delivery metrics through innovative techniques and optimization strategies.
- Demonstrated experience in gathering requirements, estimating, and managing large-scale Data Engineering projects.
- Requirement Analysis: Translate business objectives into effective data models that support long-term solutions.
- Data Modeling: Collaborate with the business team to devise data strategies, construct data flows, and create conceptual data models.
- Data Pipeline Design: Develop robust and scalable data pipelines and data products across diverse domains.
- Data Integration: Build and sustain data lakes by sourcing data from both primary and secondary channels, alongside creating scripts that enhance the flexibility and scalability of our data evaluation processes.
- Testing: Establish and oversee data loading procedures to filter out datasets or points that fall short of business rules and quality standards.
- Deployment: Execute data strategies and develop physical data models in conjunction with development teams, data analysts, and information systems teams to ensure effective operational data management systems.
- Familiarity with Data Engineering principles and best practices is essential.
- Coordinate with cross-functional teams to prioritize projects, driving strategy, roadmaps, and the execution of critical data engineering initiatives.
- Stakeholder Management: Engage with stakeholders across the organization to comprehend their data requirements and deliver tailored solutions.
- Continuous Integration and Continuous Deployment (CI/CD): Implement and maintain CI/CD pipelines for data solutions, ensuring swift, reliable, and seamless updates to the data environment.
This is a hybrid position. The expectation for in-office days will be confirmed by your hiring manager.