Director, Data Quality

How you will help

As a Director, Data QA, you will define strategy and roadmap for data quality as well as key quality metrics at the project, data load, and warehouse levels, ensuring these metrics can be shared with internal and external stakeholders to build trust in our processes and controls. As a vital contributor to the Data Operations leadership team, you will lead the Data Quality team and support its collective growth. You will develop quality standards for all HealthVerity data models and serve as a member of the HealthVerity Data Governance committee, sharing your knowledge and experience to enhance the broader data team's expertise.

What you will do

• Create a data quality strategy that aligns with the corporate strategy
• Provide strategic direction on data quality tooling and reporting
• Lead a team of data quality engineers to ensure career development and inclusive culture
• Work with customers to understand their project’s data powered needs and meet with them regularly to update progress and address blockers
• Work with the data solution’s team and other stakeholder requirements and perform internal discovery to ensure those efforts are produced at a high quality
• Provide subject matter expertise around data interpretation, mapping, and normalization
• Work with stakeholders to define data requirements for new product/data package releases
• Work with the Data Management & Analytics team to define quality control procedures, and help them define individual QA steps and needs
• Compose internal and external documentation, including workflows and technical specification
• Work with technical resources and cross functional peers to ensure department and stakeholder expectations are met
• Present to internal stakeholders, and executive management on key initiatives and department needs
• Work with QA and technical resources to organize test plans for new/custom features

How success is defined

• Quality Metrics and Strategy: Implementing key quality metrics aligned with corporate strategy and directing data quality tooling and reporting
• Leadership and Development: Leading and developing a data quality team, fostering an inclusive culture, and ensuring collaboration across departments
• Stakeholder Collaboration: Engaging with customers and stakeholders to meet data needs, update progress, and ensure high-quality outcomes
• Documentation and Communication: Producing clear documentation and effectively presenting key initiatives to stakeholders and management
• Testing and Assurance: Coordinating test plans and ensuring new features meet quality standards before release

Required skills and experience

• BS degree in management, communications, math, statistics, Information systems
• 4+ years’ experience in the data industry, preferably in a big data environments
• 2+ years of team management experience
• Strong understanding of data management principles, data governance and data quality best practices
• Experience with observability tools (e.g., Montecarlo, Metaplane, Acceldata) and data monitoring frameworks
• Hands-on experience with data validation tools (e.g., Great Expectations, dbt, Apache Airflow)
• Proficient in SQL, Python and other relevant programming languages used for data manipulation and analysis
• Experience implementing automated anomaly detection systems to proactively identify data quality issues such as missing, inconsistent, or outlier data in real time
• Establish and optimize threshold-based and machine learning-driven alerts for anomalies in data volume, schema changes, latency and distribution patterns
• Continuously improve anomaly detection algorithms by incorporating historical patterns, statistical models, and advanced machine learning techniques
• Stay updated on the latest advancements in observability, AIOps, and anomaly detection to recommend cutting-edge tools and strategies

Base salary for the role is commensurate with experience and can range between $70,000 - 190,000 + annual bonus opportunity.