In this position you will....
play a key role in building and maintaining a high-integrity data ecosystem by applying agentic AI principles to proactively improve data quality, completeness, and trustworthiness across critical datasets. Acting with autonomy and initiative, you’ll collaborate with cross-functional stakeholders to identify data gaps, implement validation frameworks, and develop intelligent monitoring solutions.
With a strong foundation in data analytics and an eye for detail, you’ll not only ensure the accuracy and reliability of reporting but also enable scalable, AI-driven processes that reduce manual effort and improve decision-making. You’ll own the design and execution of automated data quality checks, anomaly detection systems, and self-healing data pipelines that align with business goals.
You will work closely with Data Engineers, BI Analysts, and Product Owners to translate ambiguous problems into structured data solutions—enabling teams to act faster, with better data.
You will be responsible for…
- Lead the data analytics team in collecting, cleaning, and validating data from diverse internal and external sources.
- Create advanced dashboards and reports that deliver actionable insights to stakeholders, product teams, and senior leadership.
- Design and maintain scalable data models and structures that support current and future analytics and reporting requirements.
- Proactively monitor and resolve data quality issues across platforms by applying intelligent anomaly detection and validation frameworks.
- Develop and implement automated data validation rules and self-healing mechanisms to ensure accuracy, completeness, and consistency.
- Act as a bridge between business and technical teams to translate analytical needs into robust, AI-driven solutions.
- Work closely with data engineering, product, and operations teams to map data flows and introduce quality checkpoints throughout the pipeline.
- Lead root cause analysis on recurring data issues and implement long-term solutions to prevent reoccurrence.
- Build and maintain data quality dashboards to track key data quality KPIs, issue trends, and resolution SLAs.
- Contribute to and uphold data governance initiatives by promoting adherence to data standards, definitions, and documentation practices.
- Identify opportunities for automation in data ingestion, reconciliation, and validation processes to reduce manual workload and improve reliability.
- Own the tracking, prioritization, and resolution of data quality tickets, ensuring timely closure through collaboration with cross-functional teams.
- Support data migration and system integration projects by ensuring continuity, completeness, and accuracy of data across platforms.
- Leverage agentic AI principles to autonomously detect, act on, and communicate data quality improvements, increasing trust and speed in decision-making.
- Communicate complex data quality issues and solutions to both technical and non-technical stakeholders with clarity and business relevance.
For you to be successful…
We expect you to be able to demonstrate the following key competencies
Impactful
- Holds high standards for delivery of outcomes with a lens of continuous improvement. Establishes metrics and measures progress.
- Committed to delivering strategically aligned objectives, creates plan to achieve with key milestones and measures
Collaborate
- Develops strategic relationships and networks across the organization and shares with others for mutual benefit
- Manages conflict respectfully and effectively, provides constructive feedback and looks for/ proposes middle ground solutions.
Communication
- Communication is clear and concise and uses data relevant to the audience to support points of view and suggestions
- Communicates succinctly and fosters a fact-based environment where communication is backed by research and data appropriate for the audience
Adaptable
- Successfully manages rapidly changing requirements/ evolving circumstances and brings fresh ideas and innovative approaches to achieve outcomes
- Anticipates and is proactive in adapting own and team’s approach in response to changes in the strategic and/or operational direction of the organization
You will require the following qualifications and skills
- Bachelor’s degree in Data Science, Business Analytics, Computer Science, or a related field (Master's preferred).
- 7+ years of experience in data analytics, with demonstrated ownership of data quality initiatives.
- Experience in the insurance or financial services industry is a plus.
- Proven expertise in data validation, root cause analysis, and building data quality frameworks.
- Hands-on experience with SQL and Python for data manipulation, cleaning, and automation.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud is preferred.
- Proficiency in data visualization tools such as Power BI or Tableau to create intuitive dashboards and quality tracking reports.
- Strong understanding of data modeling concepts, ETL pipelines, and structured/unstructured data systems.
- Familiarity with data governance frameworks, metadata management, and regulatory compliance (e.g., GDPR).
- Ability to work independently, take initiative, and deliver high-impact solutions in a dynamic, fast-paced environment.
- Excellent communication skills with the ability to explain technical findings to non-technical stakeholders clearly and effectively.
- Experience collaborating with cross-functional teams, including data engineering, product, and operations.
- Knowledge of agentic AI tools and approaches (e.g., autonomous agents for anomaly detection, self-correcting pipelines) is a strong plus.