Lead Data Quality & Automation Specialist

• Collect, process, cleanse, and validate data from multiple internal and external sources.

• Define, maintain, and improve data rules, mappings, transformations, and interface requirements.

• Identify, investigate, and resolve data discrepancies across systems to improve accuracy, consistency, and reliability.

• Monitor data quality, hierarchy integrity, and matching outcomes; recommend scalable corrective actions and logic improvements.

• Support production data processes across the lifecycle, including pre-production validation, production issue resolution, and post-production monitoring.

• Partner with business, analytics, and technology teams to ensure trusted data supports reporting, segmentation, and decision-making.

• Contribute to automation and advanced data quality initiatives that reduce manual rework, operational risk, and downstream escalations.

• Translate data issues into business impact and prioritize improvements that enhance efficiency, accuracy, and scalability.

Requirements

• Experience working in complex, multi-source enterprise data environments.
• Strong knowledge of data quality, data governance, hierarchy management, and account or customer matching concepts.
• Ability to analyze root causes, assess downstream impacts, and implement durable data quality improvements.
• Experience supporting production data environments with a focus on stability, scalability, and issue resolution.
• Demonstrated proficiency using SQL (Snowflake preferred but SQL Server, Oracle, and Teradata are also relevant), analytical or data tools such as Python to analyze data, validate outputs, and resolve complex data issues; AI tool experience is a plus.
• Strong collaboration, communication, and prioritization skills across business, analytics, and technology teams.
• Experience supporting automation or AI/ML-enabled data maintenance initiatives is a plus.

🔍 ATS Optimization Keywords
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Hard Skills

• data cleansing
• data validation
• data governance
• data quality
• SQL
• Python
• automation
• AI
• data mapping
• data transformations

Soft Skills

• collaboration
• communication
• prioritization
• problem-solving
• analytical thinking
• root cause analysis
• stakeholder engagement
• adaptability
• attention to detail
• critical thinking