Senior Data Quality Engineer
6314 Remote/Teleworker US, United States
Full Time Senior-level / Expert USD 112K - 203K
Leidos
Leidos is an innovation company rapidly addressing the world's most vexing challenges in national security and health. Our 47,000 employees collaborate to create smarter technology solutions for customers in these critical markets.Leidos Chief Information Office within the Digital Modernization Sector is looking for a skilled and detail-oriented Senior Data Quality Engineer to join our CIO Services team. In this position, you will be responsible for ensuring the quality and integrity of our data assets. Your responsibilities will include developing and executing data quality strategies, validating data quality, and identifying opportunities for improvement.
Primary Responsibilities:
Design, implement, and maintain data quality frameworks and processes.
Develop data validation rules and monitoring dashboards to assess data accuracy and consistency.
Conduct data profiling to analyze data quality and identify anomalies.
Collaborate with data engineers, data analysts, and business stakeholders to understand data requirements and ensure alignment on data quality standards.
Perform root cause analysis on data quality issues and lead remediation efforts.
Develop and maintain documentation related to data quality rules, processes, and standards.
Create and deliver training to teams on data quality best practices.
Define and manage data quality metrics (completeness, uniqueness, consistency, timeliness, accuracy, validity) and implement scorecards.
Design automated data quality checks within data pipelines and monitor at scale.
Evaluate and tune data quality rules using Collibra Data Quality (CDQ), including rule authoring and job orchestration.
Partner with AI/ML teams to ensure high-quality training data and provide data quality assessments for machine learning models.
Basic Qualifications:
Bachelor’s degree in Computer Science or related field and 12+ years of data quality or data analysis relevant experience, Master's degree and 10+ years, Associate and 14+ years or equivalent relevant work experience may be considered in lieu of degree.
US citizenship is required.
Prior experience implementing a Data Quality Program is required
Proficiency in data profiling, data cleansing, and ETL processes.
Strong SQL skills for querying databases and validating data.
Experience with Collibra Data Quality (CDQ) or similar platforms (e.g., Informatica DQ, Talend DQ).
Demonstrated understanding of statistics and machine learning.
Familiarity with data governance concepts and best practices.
Excellent analytical and problem-solving skills.
Demonstrated ability to meet deadlines and communicate progress
Strong communication and collaboration abilities.
Preferred Qualifications:
Experience working with structured, semi-structured, and unstructured data
Data Science and AI training
Experience implementing or operating Collibra Data Quality, including policy management, scorecards, and workflow integrations.
Familiarity with Collibra Data Intelligence Platform, including metadata management and stewardship.
Exposure to AI/ML projects where data quality directly impacted model outcomes or training effectiveness.
Knowledge of Python or other scripting languages to automate data validation or integrate with ML pipelines.
Understanding of cloud data platforms (e.g., Snowflake, AWS, Azure, GCP) and how data quality frameworks integrate with them.
Perform cost analyses of data quality jobs and ensure the use of the data quality tool stays within budget for each customer.
Original Posting:
July 7, 2025For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $112,450.00 - $203,275.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Tags: AWS Azure Computer Science Data analysis Data governance Data pipelines Data quality ETL GCP Informatica Machine Learning ML models Pipelines Python Snowflake SQL Statistics Talend Unstructured data
Perks/benefits: Career development Equity / stock options
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