Randstad Digital Americas · 7 hours ago
Data Quality Engineering & Operations Manager
United States
Contract
Remote
Senior Level
$65/hr - $75/hr
7+ years expRandstad Digital Americas is offering a contract opportunity for a Data Quality Engineering & Operations Manager. This role involves leading the design, delivery, and operation of enterprise data quality capabilities, ensuring data is accurate, complete, timely, and trusted across various systems and platforms.
Information Technology & Services
Responsibilities
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
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:
Source and operational datasets
Curated analytics and semantic layers
AI training, feature, and inference pipelines
Own day-to-day data quality operations, including alert triage, root cause analysis, and remediation coordination
Establish and operationalize data quality standards for:
Critical data elements (CDEs) used in decision-making
Management and regulatory reporting datasets
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
Establish and operationalize data quality standards for AI and ML use cases, including:
Training and validation data completeness and representativeness
Label accuracy and consistency
Schema, volume, and distribution drift detection
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
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
Qualification
Required
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)
Preferred
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
Benefits
Medical
Prescription
Dental
Vision
AD&D
Life insurance offerings
Short-term disability
401K plan
Company
Randstad Digital Americas
Randstad Digital is a trusted digital enablement partner that facilitates accelerated transformation for businesses by providing global talent, capacity, and solutions across specialized domains.
10001+ employees
Funding
Current Stage
Late StageLeadership Team
Graig Paglieri
CEO, Randstad Digital Americas
Pascal de Hesselle
SVP, Executive Client Partner - Technology, Media & Telecom
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