> Markdown version of [/jobs/ext/3952259-data-quality-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/3952259-data-quality-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Quality Analytics Engineer - **Company:** Gravity It - **Location:** Doral, FL, United States - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Information Systems, Data Discovery, Information Engineering, Data Governance, Data Profiling, Data Security, Meta-Data Management, DataOps, Software Construction, SQL Databases, Enterprise Data Management, Cloud Platform System, Data Classification, Claude Code, Snowflake, Agentic-AI, Git, Core Data, Information Technology, Data Lineage, Data Management, Dynamic Data, Model Context Protocol, Software Version Control - **Published:** October 27, 2026 - **Apply:** https://www.thejobnetwork.com/job/0a437ccb-e925-41c3-8c38-7c8ae429675c/data-quality-analytics-engineer ## About the Role * 5-7 years of experience in analytics, data engineering, data quality, or data management, including hands-on delivery on analytics projects and exposure to data quality, master data management, and/or data protection initiatives \n * Strong proficiency in SQL and Python for data analysis, quality rule development, and reconciliation across relational and cloud-native platforms \n * A genuine proponent of data quality and data trust practices - someone who argues for the right fix rather than the fast one, and can explain why it matters to a non-technical audience \n * Working knowledge of core data quality concepts: profiling, rule authoring, exception management, reconciliation, and quality metrics \n * Understanding of master data management fundamentals - matching, survivorship, golden records, and hierarchy management \n * Awareness of data protection concepts: sensitive data classification, masking, least-privilege access, and the regulatory drivers behind them \n * Demonstrated ability to turn data into analytics people act on - dashboards, scorecards, or reporting products with a real audience \n * Solid understanding of data governance principles, data cataloging, metadata management, and data lineage \n * Experience defining data quality metrics and SLAs and reporting on data health to senior stakeholders \n * Ability to work collaboratively with business users, data stewards, and technical teams to gather requirements and deliver solutions \n * Strong adherence to software engineering best practices including version control (git), modular code design, Agile methodologies, and CI/CD pipelines \n * Curiosity and speed in learning emerging data quality and AI technologies, and comfort adapting to an evolving enterprise data landscape \n * Bachelor's degree in computer science, Information Systems, Data Science, or a related field; equivalent practical experience will be considered \n, * Hands-on experience with a data quality platform such as Atacama ONE or Ataccama DQ for data profiling, quality rule authoring, and workflow management \n * Demonstrated experience implementing or managing Master Data Management solutions - Reltio strongly preferred \n * Exposure to data protection or data security tooling such as Varonis, including sensitive data discovery and access analytics \n * Proficiency with Snowflake, including data quality patterns, dynamic data masking, and Snowflake's native data quality features \n * Experience working in AWS cloud environments and with services relevant to data quality and governance (S3, Glue, Lambda, Step Functions) \n * Ability to build and use MCP (Model Context Protocol) connections to wire AI agents into enterprise data and tooling \n * Familiarity with agentic AI on AWS Bedrock, and experience with AI development assistants such as Claude Code or Codex, applied to automating data operations workflows \n * Experience working with regulated or privacy-sensitive data domains \n ## Description 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.