Data Quality Analytics Engineer

Job: Data Quality Analytics Engineer
Location: Miami FL OR Irving, TX (3 days onsite and 2 days remote)
Job Type: Contract to Hire

What We Are Looking For
Every AI decision we make is only as good as the data underneath it. This role owns whether that data can be trusted - and makes that trust visible to the people betting on it.

The Data Quality Analytics Engineer sits at the intersection of four disciplines most companies keep in separate silos: data quality, master data management (MDM), data protection, and analytics. This position is part of the Data & AI team, which exists to turn data into better business outcomes and weave those insights into the company’s corporate fabric. You will design and operationalize enterprise-grade data quality and MDM frameworks, extend them into how sensitive data is classified and protected, and build the analytics that tell the organization how healthy its data actually is.

You will also get to work at the front edge of applied AI - using AWS Bedrock, agentic AI patterns, and MCP connections to automate data trust monitoring and remediation at a scale no manual process can reach. If you like solving problems that are equal parts engineering, analytics, and detective work - and you care about getting the answer right - this is a good seat.

Responsibilities

• Design and operationalize end-to-end data quality frameworks - profiling, cleansing, validation, and continuous monitoring - across the enterprise data estate
• Make data trust visible through analytics: build data quality scorecards, executive dashboards, and self-service views that show business teams the health of the data behind their decisions
• Partner with analytics and BI teams to translate analytics use cases into data quality requirements, so trust is designed in upstream rather than patched downstream
• Configure and manage Master Data Management (MDM) solutions to create and maintain golden records for critical business entities such as customers, products, vendors, and properties
• Deploy and administer data quality and MDM platforms (for example Ataccama ONE and Reltio) to enforce quality rules, lineage tracking, and issue resolution workflows
• Extend the data quality practice into data protection - partner with security and privacy teams on sensitive data discovery, classification, masking, and access monitoring using tools such as Varonis
• Develop and maintain SQL- and Python-based data quality rules, reconciliation logic, and automated validation across structured and semi-structured sources
• Build and maintain data quality pipelines in Snowflake and AWS cloud environments, leveraging native features for scalable quality checks and anomaly detection
• Prototype and product ionize agentic AI workflows - using AWS Bedrock, MCP connections, and modern AI development tools - to automate profiling, issue triage, root cause analysis, and self-healing remediation
• Define and track data quality KPIs and SLAs; report data health clearly to both business and technology stakeholders
• Lead data quality issue triage, root cause analysis, and remediation in collaboration with upstream data owners and platform teams
• Partner with data governance, data engineering, and business teams to establish enterprise data standards, taxonomies, and ontologies
• Support CI/CD practices for data quality rule deployment, version control, and automated regression testing
• Contribute to data quality, MDM, and data protection policies, standards, and best-practice documentation
• Champion a culture of data trust across the organization through training, evangelism, and hands-on enablement of data consumers and producers

Required Qualifications

• 5-7 years of experience in analytics, data engineering, data quality, or data management, including hands-on…