Technical Data Quality Engineer presso Comerica Bank
Comerica Bank · Auburn Hills, Stati Uniti d'America · Onsite
- Professional
- Ufficio in Auburn Hills
Technical Data Quality Engineer
The Technical Data Quality Engineering role will support the Data Quality lifecycle from inception to implementation through various distribution channels. This role will ensure data accuracy, consistency, and reliability by establishing data quality rules and standards, monitoring data health, and resolving issues using technical tools and analytical methods. Responsibilities include data profiling, cleansing, reporting on data quality metrics, and collaborating with data engineers, the Data Governance team, and business teams to improve data governance and data integrity across the organization. Key skills involve SQL, programming, data visualization, statistical analysis, and understanding data quality methodologies to ensure data accuracy and support informed decision-making. This role will also have significant ownership of the ultimate success of Data Quality throughout the data life cycle.
Design and Methodology
- Design, implement and operate medium to large-scale, high-volume, high-performance data structures for reporting, analytics, and data science.
- Write and refine code to ensure performance and reliability of data extraction and processing.
- Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging big data tools.
- Create data products for analytics and Data Scientist team members to improve their productivity.
- Document and test moderate data systems that bring together data from disparate sources, making it available to Data Scientists, and other users using scripting and/or programming languages.
- Design, develop and build real-time data pipelines from a variety of sources (streaming data, APIs, data warehouse, messages etc.)
- Leverage the understanding of software architecture and software design patterns to write scalable, maintainable, well-designed, and future-proof software.
- Manage existing pipelines and create new pipelines from a variety of sources (relational, XML, etc.)
- Design and build solutions to track data quality, stabilize data pipeline, etc. to ensure reliable operations.
- Document and test data processes including performance of through data validation and verification.
- Gather business and functional requirements and translate these requirements into robust, scalable operable solutions with a flexible and adaptable data architecture.
- Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.
- Collaborate with Data Scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.
- Coordination with other teams to design optimal patterns for data ingest and egress, as well as lead and coordinate data quality initiatives and troubleshooting.
- Participate in sprint planning meetings as needed.
- Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
- Optimize support for ad-hod analysis across various data sources.
- Ensure best practices are followed across architecture, codebase, and configuration.
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.
- In collaboration with the Data Engineer III, contribute to the exploration and understanding of new tools and techniques for improvements to the data pipeline.
- Review and are familiar with automated processes for performance and fault tolerance.
- Review functional and technical designs to identify areas of risk and any missing requirements.
- Design and implement security measures to protect data from unauthorized access or misuse.
- In collaboration with the Data Engineer III, design backup and recovery procedures to ensure data integrity is maintained.
- Keeps management informed of status of on activities through accurate, timely, and appropriate reporting.
- Contribute to Data Governance, system documentation and sharing of data asset knowledge.
- Actively participates in committees representing the department and/or planning unit.
- Keeps abreast of leading-edge technologies in the Data Engineering space.
