Abacus Insights - Senior Data Governance & Quality Engineer
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Requirements
• Transform How We Deliver: Redesign and standardize delivery methodologies, governance, and controls to drive consistency, predictability, and operational excellence across all projects. • Transform How We Deliver: • Lead with Data & Insight: Build a metrics‑driven operating model using KPIs such as cycle time, cost‑to‑deliver, quality, and client outcomes to proactively manage risk and performance. • Lead with Data & Insight: • Partner at the Executive Level: Work closely with Client Success, Product, Engineering, and Finance to manage scope decisions, align priorities, and resolve escalations with clarity and confidence. • Partner at the Executive Level: • Scale Global Teams: Lead and mentor high‑performing teams across geographies, fostering a culture of accountability, continuous improvement, and client focus. • Scale Global Teams: • Optimize Resources: Oversee delivery capacity planning and resource allocation, balancing client demand with available talent while identifying risks and tradeoffs early. • Optimize Resources: • Embed Operational Rigor: Ensure every aspect of delivery—from project initiation through completion—is insight‑driven, well‑governed, and designed to scale. • Embed Operational Rigor: • Champion Knowledge & Learning: Build and maintain strong knowledge‑management practices so teams can easily access playbooks, lessons learned, and client insights. • Champion Knowledge & Learning: • A strong foundation in healthcare payer operations, with experience supporting regional health plans and/or Blue plans. • Minimum of 10 years of experience in delivery, operations, project management, or related roles, including senior leadership responsibility. • Proven success leading large, distributed, global teams and driving results through influence, clarity, and trust. • A track record of transforming delivery organizations—improving efficiency, quality, and client outcomes through process redesign and automation. • Experience leveraging GenAI and modern tooling to enhance operational workflows and delivery execution. • Exceptional executive presence and communication skills, with the ability to navigate complex stakeholder and client conversations. • A data‑driven mindset with strong analytical capabilities and the ability to translate insights into action. • Comfort operating in a fast‑paced, scaling SaaS environment, balancing strategic thinking with hands‑on execution. • Bachelor’s degree in Business, Operations, or a related field; Advanced degrees are welcomed but not required. • Compensation: Compensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants.
Responsibilities
• Data Quality Framework Development: Develop, implement, and sustain a comprehensive data quality framework to systematically monitor, validate, and enhance data accuracy and consistency throughout all systems. Develop and maintain scalable data quality solutions utilizing Databricks and Apache Spark, primarily leveraging PySpark. • Data Quality Framework Development: • Governance & Compliance: Operationalize the enterprise data governance framework, aligning with stakeholder needs related to data quality, access controls, compliance, privacy, and security. • Governance & Compliance: • Data Monitoring & Auditing: Identify and address data anomalies, inconsistencies, duplicates, and missing values. Conduct periodic audits to ensure ongoing data integrity. • Data Monitoring & Auditing: • Cross-Functional Collaboration: Partner with data engineers, architects, product teams, and analysts to define data quality requirements and ensure alignment with business objectives. • Cross-Functional Collaboration: • Insight Generation: Develop clear and actionable dashboards and reports (e.g., Power BI, Salesforce) to visualize data quality trends, KPIs, and issue resolution progress. • nsight Generation: • Root Cause Analysis: Collaborate with data stewards and product owners to investigate and resolve data quality issues, establishing sustainable remediation processes. • Root Cause Analysis: • Technical Expertise: Apply strong understanding of data models (e.g., star schema, snowflake, data marts, data lakes) to evaluate and improve data structures and flows. • Technical Expertise: • Process Ownership: Take ownership of assigned initiatives, break complex challenges into manageable components, and execute plans effectively with minimal supervision. • Process Ownership:
Benefits
• What you’ll get in return • Unlimited paid time off – recharge when you need it • Work from anywhere – flexibility to fit your life • Comprehensive health coverage – multiple plan options to choose from • Equity for every employee – share in our success • Growth-focused environment – your development matters here • Monthly cell phone allowance – stay connected with ease #LI-RF1 #LI-Remote
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