Lead Data Analysis
About The Position
Lead Data Analysis professionals are responsible for ensuring the accuracy, integrity, and usability of enterprise data across multiple business applications and repositories. This role focuses on data collection, processing, mapping, quality improvement, discrepancy resolution, and interface support to maintain trusted data foundations. The position enables downstream reporting, analytics, and business decision-making by improving data reliability at scale. This role is centered on improving and maintaining trusted enterprise data rather than owning dashboards or visualization deliverables. The Lead Data Analysis position supports data quality, governance, integrations, lifecycle management, and scalable issue resolution so business and analytics teams can rely on accurate data.
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.
- Strong collaboration, communication, and prioritization skills across business, analytics, and technology teams.
Nice To Haves
- AI tool experience is a plus.
- Experience supporting automation or AI/ML-enabled data maintenance initiatives is a plus.
Responsibilities
- 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.
Benefits
- Medical/Dental/Vision coverage
- 401(k) plan
- Tuition reimbursement program
- Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
- Paid Parental Leave
- Paid Caregiver Leave
- Additional sick leave beyond what state and local law require may be available but is unprotected
- Adoption Reimbursement
- Disability Benefits (short term and long term)
- Life and Accidental Death Insurance
- Supplemental benefit programs: 8critical illness/accident hospital indemnity/group legal
- Employee Assistance Programs (EAP)
- Extensive employee wellness programs
- Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone
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What This Job Offers
Job Type
Full-time
Career Level
Senior
