Data Quality Manager

Overview

Remote
$100,000 - $140,000
Full Time

Skills

ETL
SQL
Python
QA

Job Details

What You ll Do

  • Lead and mentor a team of Data Quality Engineers responsible for testing and validating data pipelines, ETL processes, and data warehouse systems
  • Define and enforce data quality standards, governance policies, and best practices across the organization
  • Collaborate cross-functionally with data engineers, product managers, analysts, and business stakeholders to ensure data integrity and high availability
  • Design and oversee the implementation of scalable test strategies, automation frameworks, and continuous integration pipelines
  • Review and approve complex SQL queries and data validation scripts developed by the team
  • Guide the team in writing test cases for traditional RDBMS and cloud-native platforms like Snowflake and Redshift
  • Support release planning by estimating test scope, timelines, and resource needs
  • Drive proactive identification and resolution of data quality issues before they impact analytics or reporting
  • Provide thought leadership in test automation for big data and streaming environments
  • Facilitate UAT cycles and ensure alignment between technical requirements and business expectations
  • Foster a culture of quality, accountability, and continuous improvement

What You Will Need

  • Proven experience in managing and scaling data quality engineering teams in agile environments
  • Deep understanding of test automation architecture, frameworks, and scripting languages (Python, Bash, etc.)
  • Expertise with SQL and orchestration tools such as Apache Airflow, Luigi, or SQL Agent
  • Strong knowledge of ETL tools (Informatica, Ab Initio, Talend) and reporting platforms (Power BI, Tableau)
  • Hands-on experience with traditional databases (MySQL, Postgres, SQL Server) and cloud data warehouses (Snowflake, Redshift)
  • Experience with test management and agile tools (Jira, Rally, HP ALM)
  • Track record of implementing CI/CD processes using Jenkins, GitLab, or Maven
  • Ability to interpret data models, ER diagrams, and complex schemas to inform validation strategies
  • Familiarity with Kafka messaging, REST APIs, and containerized environments (Docker, Kubernetes) is a plus
  • Excellent leadership, communication, and problem-solving skills

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