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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Quality Analytics Engineer - **Company:** Akaasa Technologies - **Location:** Irving, TX, United States - **Experience:** Expert - **Salary:** $125,760.0 - $188,640.0 - **Contract:** Permanent contract - **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, Snowflake, Git, Core Data, Information Technology, Data Lineage, Data Management, Dynamic Data, Software Version Control - **Published:** September 5, 2026 - **Apply:** https://www.careerjet.com/jobad/us80f03c5e5d7a6ddcd9a2f7517e9327e8 ## About the Role Education and Experience Requirements: Required: * 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 * Strong proficiency in SQL and Python for data analysis, quality rule development, and reconciliation across relational and cloud-native platforms * 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 * Working knowledge of core data quality concepts: profiling, rule authoring, exception management, reconciliation, and quality metrics * Understanding of master data management fundamentals - matching, survivorship, golden records, and hierarchy management * Awareness of data protection concepts: sensitive data classification, masking, least-privilege access, and the regulatory drivers behind them * Demonstrated ability to turn data into analytics people act on - dashboards, scorecards, or reporting products with a real audience * Solid understanding of data governance principles, data cataloging, metadata management, and data lineage * Experience defining data quality metrics and SLAs and reporting on data health to senior stakeholders * Ability to work collaboratively with business users, data stewards, and technical teams to gather requirements and deliver solutions * Strong adherence to software engineering best practices including version control (git), modular code design, Agile methodologies, and CI/CD pipelines * Curiosity and speed in learning emerging data quality and AI technologies, and comfort adapting to an evolving enterprise data landscape * Bachelor's degree in Computer Science, Information Systems, Data Science, or a related field; equivalent practical experience will be considered Preferred - Nice to Have: * Hands-on experience with a data quality platform such as Ataccama ONE or Ataccama DQ for data profiling, quality rule authoring, and workflow management * Demonstrated experience implementing or managing Master Data Management solutions - Reltio strongly preferred * Exposure to data protection or data security tooling such as Varonis, including sensitive data discovery and access analytics * Proficiency with Snowflake, including data quality patterns, dynamic data masking, and Snowflake's native data quality features * Experience working in AWS cloud environments and with services relevant to data quality and governance (S3, Glue, Lambda, Step Functions) * Ability to build and use MCP (Model Context Protocol) connections to wire AI agents into enterprise data and tooling * 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 * Experience working with regulated or privacy-sensitive data domains ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Got AI ideas but no money? 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