Data Quality Engineering and Operations Manager

Mandatory Skills data quality rules, data quality management, data observability, monte carlo, data quality engineering, data governance, data quality
Optional Skills data freshness, data volume, data science, data distribution, schema changes, anomaly detection, data engineering

Location: US based Reporting To: Vice President of Data Governance

Role Summary: We are seeking a Data Quality Engineering and Operations Manager to lead the design, delivery, and operation of enterprise data quality capabilities across operational systems, analytics platforms, and AI pipelines. This role sits within the Data Governance function and owns data quality as a product ensuring data is accurate, complete, timely, and trusted wherever it is used. You will own the data quality roadmap and backlog, manage a team of Data Quality Engineers, and leverage Monte Carlo as a core data observability and quality monitoring platform to detect, prioritize, and resolve data quality issues at scale.

What You ll Do Product Ownership & Strategy
Own the enterprise data quality strategy, roadmap, and backlog aligned to data governance objectives and business priorities
Define success metrics for data quality, including coverage, incident reduction, SLA performance, analytics trust, and AI impact through well-documented and enforceable policy, standard and procedures
Drive adoption and value realization of data quality policy and standards from Monte Carlo, ensuring it is used consistently and effectively across domains Delivery & Operations
Translate business, governance, analytics, and AI requirements into actionable data quality rules, thresholds, and monitoring
Configure and operationalize Monte Carlo to monitor data freshness, volume, distribution, schema changes, and anomalies

Ensure data quality controls are implemented across:
o Source and operational datasets
o Curated analytics and semantic layers
o AI training, feature, and inference pipelines

Own day-to-day data quality operations, including alert triage, root cause analysis, and remediation coordination Data Quality for Operations & Analytics
Establish and operationalize data quality standards for:
o Critical data elements (CDEs) used in decision-making
o Management and regulatory reporting datasets
o Enterprise metrics, KPIs, and dashboards

Use Monte Carlo observability signals to proactively identify upstream issues impacting reports and analytics
Improve trust and adoption of analytics through transparent quality metrics and reporting Data Quality for AI & Advanced Analytics
Establish and operationalize data quality standards for AI and ML use cases, including:
o Training and validation data completeness and representativeness
o Label accuracy and consistency
o Schema, volume, and distribution drift detection
o Bias, outlier, and feature stability monitoring
Partner with data science teams to identify AI-critical datasets and features
Use Monte Carlo monitoring and anomaly detection to identify data issues that could impact model performance or reliability People & Stakeholder Leadership
Manage and mentor Data Quality Engineers responsible for rule development, monitoring, and issue analysis
Collaborate with Data Engineering, Analytics, Data Science, Privacy, and Business Data Owners
Communicate data quality health, trends, and risks to governance and executive stakeholders

What We re Looking For
7+ years of experience in data, analytics, or data management roles with a strong focus on data quality
3+ years in a people-lead role supporting data or analytics platforms
Hands-on experience implementing or operating Monte Carlo or similar data observability platforms
Strong understanding of data quality dimensions across operational, analytical, and AI use cases
Experience working with modern data platforms (cloud data warehouses/lakehouses, ETL/ELT pipelines, BI tools)

Nice to Have
Experience working within a formal Data Governance organization
Familiarity with data observability, anomaly detection, and data drift concepts
Experience supporting AI/ML or advanced analytics use cases
Background in regulated industries Why This Role
Own and evolve an enterprise data quality capability powered by Monte Carlo
Influence how data is trusted across reporting, analytics, and AI
Operate within a mature Data Governance function with executive sponsorship
Combine product ownership, platform leadership, and team management