Data Quality Engineer

ABOUT GRADERA Gradera defines a new category of enterprise transformation called Software-Orchestrated Services™ - where software orchestrates human expertise, digital workers, and enterprise systems to deliver governed outcomes at scale. As an AI Native Services firm, we help enterprises redesign how work gets done across operations, product, engineering, customer experience, data, and enterprise workflows to move beyond fragmented AI pilots and disconnected automation toward measurable business outcomes. OVERVIEW We are seeking a detail-oriented Data Quality Engineer to ensure the integrity, accuracy, and reliability of data powering our digital twin and AI platforms. You will design and implement data quality frameworks, build automated validation pipelines, and establish quality metrics that enable trusted, simulation-ready data products. This role is critical to ensuring that operational decisions and ML models are built on a foundation of high-quality, governed data. KEY RESPONSIBILITIES - Design and implement data quality frameworks using Delta Live Tables expectations and Great Expectations - Build automated data validation pipelines that enforce quality standards at ingestion and transformation stages - Develop data profiling processes to understand data distributions, patterns, and anomalies - Define and track data quality metrics (completeness, accuracy, consistency, timeliness, validity) - Implement anomaly detection mechanisms to identify data drift and quality degradation - Create quality dashboards and alerting systems for proactive issue identification - Collaborate with data engineers to embed quality checks into ETL/ELT pipelines - Partner with data architects to establish data quality standards and governance policies - Investigate and perform root cause analysis for data quality issues - Document data quality rules, thresholds, and remediation procedures - Support data certification processes for simulation-ready and ML-ready datasets - Drive con