Lead Data Quality and Governance Analyst
About The Position
The Lead Data Quality and Governance Analyst leads data quality, governance, and data engineering initiatives to ensure enterprise data is accurate, reliable, consistent, and fit for business use. The role combines data governance expertise with hands-on technical capabilities in Splunk, Apache Kafka, ETL development, JSON, and structured, semi-structured, and unstructured data. It drives data standards, controls, monitoring, and continuous improvement. The position partners with business, technology, data engineering, and governance teams to resolve data issues and implement improvements. It also provides subject matter expertise, mentors team members, and promotes adoption of new processes and methodologies.
Requirements
- Bachelor's degree in a relevant field, such as Computer Science, Information Systems, or Data Science.
- At least 5 years of experience in data quality, data governance, data management, or data engineering.
- At least 3 years of hands-on experience with Splunk, Apache Kafka, and ETL development.
- Experience working with structured, semi-structured (such as JSON), and unstructured data.
- Experience defining and enforcing data quality rules, data controls, and data lifecycle management.
- Experience with data quality monitoring, validation, auditing, and issue remediation.
- Experience designing, documenting, and troubleshooting data integration, data flows, and transformation processes.
- Experience collaborating with business and technology stakeholders to resolve data issues and communicate findings.
Nice To Haves
- 7 or more years of work experience.
- Experience with real-time and streaming data pipelines and event-driven data processing.
- Advanced experience with high-volume data processing using Splunk, Kafka, and ETL tools.
- Experience with master data management, metadata management, data lineage, and enterprise data standards.
- Hands-on experience with Collibra, including developing data quality rules, controls, and monitoring or reporting frameworks.
- Experience building dashboards and reports for operational metrics and trend analysis.
- Experience implementing automation or process improvements that reduce manual effort or improve efficiency.
- Experience leading complex initiatives, mentoring team members, or coordinating cross-functional teams.
Responsibilities
- Lead implementation of data quality, governance, and data management standards, controls, tools, and processes.
- Monitor data quality metrics, perform data validation and audits, identify issues, and drive remediation.
- Strengthen governance and controls throughout the end-to-end data lifecycle.
- Design and support ETL and data integration processes for reliable and consistent data flows.
- Work with Kafka-based streaming and event data, JSON, and structured, semi-structured, and unstructured data.
- Use Splunk for data analysis, monitoring, troubleshooting, validation, and operational insights.
- Support master data management and enterprise data standards, and identify opportunities to improve data integrity and availability.
- Develop and enhance reports, dashboards, metrics, and trend analysis to support data-driven decisions.
- Partner with business, technology, data engineering, and governance teams to resolve data issues and implement improvements.
- Provide subject matter expertise, mentor team members, and drive adoption of new processes and methodologies.
Benefits
- A superior retirement program.
- Competitive health, wellness, and work-life offerings.
- A compensation package that may include participation in a performance-linked incentive program, depending on the role.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
