Javen Technologies, Inc

Compensation

Full Description

Title: Data Quality Product Owner - Data Quality Engineering and Operations Manager Location: Fully Remote Contract to Hire Opportunity Location: US based 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