Location / Remote: Hybrid in Cleveland, OH, 44143 (3 days per week onsite).
Employment Type: 6-month W-2 contract (possibility to extend)
Compensation: up to 90/hour W-2 (depending on experience).
Benefits: Medical, dental, vision, LTD/STD, HSA/FSA, term life, and supplemental health insurances (e.g., Aflac) for all employees (and their families if needed).
The Data Engineer plays a critical role in identifying, analyzing, and resolving data integrity issues across enterprise systems. This position focuses on investigating inconsistencies, repairing corrupted or missing data, and implementing processes to ensure accurate and reliable data propagation. Leveraging advanced SQL, debugging skills, and AI-assisted analytics, the engineer will work directly with production data to develop remediation scripts, perform root-cause analysis, and implement quality controls.
Responsibilities:
- Investigate data inconsistencies across enterprise systems and perform root-cause analysis.
- Conduct data reconciliation and lineage analysis to identify and resolve issues.
- Write SQL queries and scripts to detect and correct corrupted, missing, or misaligned data.
- Develop remediation scripts to address production data integrity issues.
- Collaborate with integration and platform teams to prevent recurring data problems.
- Implement data validation, monitoring, and quality controls to improve system reliability.
- Leverage AI-assisted analytics to accelerate anomaly detection and remediation workflows.
Required Skills:
- Advanced SQL and data analysis expertise.
- Proven experience with data reconciliation and data lineage analysis.
- Familiarity with enterprise data platforms and Azure data services (Azure SQL, Data Factory, or similar).
- Strong debugging and investigative skills for analyzing complex data flows across multiple systems.
- Hands-on experience with AI-assisted analytics or automation tools.
- Demonstrated ability to correct data integrity issues in production systems.
- Ability to analyze production data directly using SQL and analytics tools.
- Experience developing scripts to repair corrupted or inconsistent data.
- Expertise in investigating root causes of data propagation failures.
- Knowledge of implementing data validation, monitoring, and quality controls.
Preferred Skills:
- Experience leveraging AI-assisted analytics to accelerate detection and remediation processes.
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