Senior Data Engineer- Fusion Experience

Build reliable, governed data products

As a Senior Data Engineer in Cleveland, OH (onsite), you will design and deliver scalable data pipelines and data solutions that help ensure performance, security, and reliability. The work is grounded in strong data governance, validation, and quality assurance, with an emphasis on building data products that can be reused and operated day to day.

You will collaborate in an agile environment, independently and with other engineers, to develop, maintain, and debug data solutions. You will also contribute to a culture of continuous learning through feedback, training, and knowledge sharing.

Responsibilities

• Design and build data pipelines to support optimal data processing from a variety of data sources.
• Identify data requirements and project objectives in collaboration with cross-functional teams.
• Independently analyze, design, and troubleshoot data flows based on business needs.
• Translate business requirements into technical specifications.
• Adjust data collection processes using indexing and query optimizations to improve performance.
• Build Extract, Transform, and Load (ETL) pipelines to enable efficient data collection and extraction.
• Profile data sources to validate fit and pipeline build success.
• Define success and failure thresholds for data collection pipelines.
• Implement data governance policies and procedures for data handling, including data retention, to support data consistency, integrity, accuracy, and reliability.
• Redact PII and PHI to support compliance with data privacy and security standards.
• Follow data security measures to protect data from unauthorized access, use, disclosure, alteration, or destruction.
• Ensure data compliance with applicable laws, regulations, and industry standards.
• Implement data validation and integrity checks to identify and address data quality issues that could affect pipeline and model performance.
• Define data annotation and labeling processes to maintain data quality independently.
• Design and implement automation of data validation and governance.
• Independently design, develop, and optimize scalable data pipeline architectures using ETL to build reusable data products.
• Implement data storage solutions for scalable, optimized access and analysis.
• Manage the day-to-day flow of data pipelines and storage operations.
• Write runnable code, test, and debug data solutions independently.
• Manage work by monitoring timelines and deliverables to keep initiatives on track and aligned to requirements.
• Prioritize work and adapt to resource or timeline changes by suggesting adjustments to maintain efficiency.
• Collaborate across teams to align on expectations and achieve shared objectives.
• Actively listen, ask questions for understanding, and engage diverse perspectives.
• Independently address standard and non-standard issues per standard practices, escalating complex items as appropriate.
• Troubleshoot errors by analyzing data and information from multiple sources.
• Contribute to knowledge sharing and best practices.
• Seek continuous learning through new skills, tools, and staying current with industry trends; leverage feedback and training to improve.
• Recommend updates to improve efficiency and effectiveness of team processes, protocols, and workflows.
• Seek input from team members on alternative approaches and methods.

Technologies

• Extract, Transform, and Load (ETL)
• Indexing
• Query optimizations