Systems Manager, Data Quality Assurance

Overview

The Systems Manager, Data Quality Assurance, leads Con Edison's enterprise data quality program, ensuring that all data powering analytics, AI, and operational systems is accurate, complete, and trustworthy. Acting as the hands-on execution arm of data governance, this role translates enterprise data policies into enforceable quality rules, validation controls, and monitoring mechanisms embedded directly within data pipelines and platforms. The manager ensures that data supporting grid operations, asset management, forecasting, and customer analytics consistently meets defined quality standards and service-level expectations.Working in close partnership with data engineering, AI platform, governance, and business teams, this position defines and oversees data quality KPIs, thresholds, and validation frameworks across ingestion, transformation, storage, and consumption layers. The Systems Manager, Data Quality Assurance, plays a vital role in enabling reliable AI and advanced analytics by ensuring that training datasets, features, and production data meet strict quality and consistency requirements. By embedding automated data quality controls throughout the lifecycle, the manager safeguards regulatory compliance, supports explainable AI outcomes, and strengthens confidence in enterprise data-driven decisions.

- Ensure enterprise data is accurate, complete, consistent, and trustworthy across all platforms and business use cases

- Define and maintain ingestion validation rules, acceptance criteria, and data quality thresholds across raw, curated, and consumption layers

- Validate transformation logic and data processing against approved business rules, definitions, and compliance requirements

- Develop, own, and govern enterprise data quality rules, KPIs, and metrics by data domain, ensuring consistent standards and accountability

- Monitor data quality dashboards, alerts, exceptions, and remediation progress to maintain SLA adherence and reliability

- Govern business metadata, ownership models, and golden records to maintain authoritative, auditable, and well-defined data assets

- Define and enforce data access policies, privacy requirements, and compliance-related controls in alignment with enterprise governance

- Collaborate with Data Engineering, AI Platform, and Governance teams to embed automated data quality validations within data pipelines

- Validate correctness and consistency of datasets used for analytics, machine learning, and AI model development and production

- Support regulatory, audit, and compliance reviews by monitoring data quality trends, risks, and recurring issues to drive continuous improvement

- Lead and develop a team through coaching, performance management, and effective work assignment to drive aligned execution and business outcomes

Qualifications

Required Education/Experience

- Master's Degree and a minimum of 6 years full-time relevant work experience or

- Bachelor's Degree and a minimum of 8 years full-time relevant work experience.

Preferred Education/Experience

- Master's Degree in Business Administration, Finance, Accounting, Management Information Systems, Information Systems, related business or technology aligned field and a minimum of 6 years full-time relevant work experience.

Relevant Work Experience

- Demonstrated experience leading enterprise data quality programs in large scale, regulated environments supporting analytics, AI, and operational systems, preferred

- Proven hands-on experience translating enterprise data governance policies into enforceable data quality rules, validation controls, and monitoring frameworks, preferred

- Strong background defining, implementing, and managing data quality KPIs, thresholds, and service level expectations across the full data lifecycle, preferred

- Experience embedding automated data quality checks and validation mechanisms within data ingestion, transformation, storage, and consumption pipelines, preferred

- Demonstrated ability to ensure data supporting grid operations, asset management, forecasting, and customer analytics meets consistent accuracy, completeness, and reliability standards, preferred

- Proven track record partnering closely with data engineering, AI platform, governance, and business teams to operationalize data quality at scale, preferred

- Experience supporting AI and advanced analytics initiatives by ensuring training data, features, and production datasets meet strict quality and consistency requirements, preferred

- Strong understanding of regulatory compliance, auditability, and explainability requirements related to enterprise data and AI driven decisions, preferred

- Demonstrated experience implementing monitoring, alerting, and issue resolution processes for data quality defects and anomalies, preferred

- Ability to communicate data quality posture, risks, and improvement progress to technical teams and senior leadership, preferred

Skills and Abilities

- Strong written and verbal communication skills

- Builds and manages effective teams

- Ability to work within tight timeframes and meet strict deadlines

- Ability to work within tight timeframes and meet strict deadlines

Licenses and Certifications

- Driver's License Required

- Project Management Professional (PMP) Preferred

- Certified Project Management (CPM) Preferred

- Other: GCP Professional Certification Preferred

- Other: Databricks Professional Certification Preferred

Physical Demands

- Sit or stand to use a keyboard, mouse, and computer for the duration of the workday

Additional Physical Demands

- The selected candidate will be assigned a System Emergency Assignment (i.e., an emergency response role) and will be expected to work non-business hours during emergencies, which may include nights, weekends, and holidays.