Data Quality Engineer - MVP Group Inc

About MVP:

Headquartered in the heart of Austin, Texas, MVP is the best-in-class SaaS measurement platform that provides omnichannel media and sponsorship valuation. We offer a built-to-scale software for our clients--Fortune 1,000 brands, professional sports, global agencies and media--to accurately quantify the value of their partnerships, sponsorships, and activations.

About the Role:

We’re looking for a talented Data Quality Engineer to join our growing team and play a critical role in ensuring that the data powering our platform is accurate, reliable, and trusted by our customers. If you are passionate about data, automation, and building high-quality systems, this is your opportunity to make a real impact!

As a Data Quality Engineer, you will be responsible for designing and implementing solutions that ensure the accuracy, integrity, and reliability of our data. Working closely with data engineers, product teams, and data analysts, you will help build and maintain systems that proactively monitor, validate, and improve the quality of our data across the entire lifecycle.

Your expertise in data quality, automation, and attention to detail will be instrumental in building robust processes and frameworks that safeguard our data, enabling us to deliver exceptional products and insights to our customers.

Key Responsibilities:

• Data Quality Assurance:
  • Design and implement automated data quality checks to validate data accuracy, completeness, consistency, and reliability at every stage of the data pipeline.
  • Create and maintain data validation frameworks and tools to automatically identify data anomalies, errors, and inconsistencies.
  • Build automated alerts, monitoring dashboards, and reports that provide visibility into data quality metrics, and trigger timely responses to issues.
• Collaboration & Problem Solving:
  • Partner with data engineers, data scientists, and product teams to define data quality requirements, understand data pipelines, and ensure data meets the highest standards.
  • Investigate and troubleshoot data quality issues, working closely with teams to identify root causes and implement corrective actions.
  • Provide guidance on best practices for data quality and governance, helping teams align on data standards and processes.
• Process Improvement & Automation:
  • Continuously assess and improve existing data quality processes, recommending automation where possible to reduce manual oversight and accelerate issue detection.
  • Leverage tools and frameworks to automate repetitive tasks, optimize data quality workflows, and reduce time spent on manual data validation.
  • Drive continuous improvement by staying up-to-date with emerging data quality tools, techniques, and best practices.
• Data Monitoring & Metrics:
  • Develop key performance indicators (KPIs) and metrics that measure the health and quality of our data.
  • Create and maintain real-time dashboards that track data quality trends, highlighting areas of concern and success.
  • Perform regular data audits and provide data quality reports to stakeholders across the company.
• Proactive Data Governance:
  • Ensure data is compliant with internal and external standards, regulations, and policies, particularly when dealing with sensitive or personally identifiable information (PII).
  • Help implement data governance frameworks and practices to enhance data stewardship across the organization.
  • Advocate for a data-driven culture that values data quality and promotes transparency in data handling.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field (or equivalent practical experience).
• Experience:
  • 3+ years of experience in data engineering, data quality, or related roles, preferably within a SaaS or data-intensive environment.
  • Proven experience designing, building, and maintaining automated data quality frameworks and tools.
  • Strong understanding of data pipelines, ETL processes, and data warehousing technologies (e.g., SQL, Snowflake, Redshift, BigQuery).
  • Experience with data validation tools and frameworks (e.g., Great Expectations, Deequ, or custom-built solutions).
  • Familiarity with cloud platforms (AWS, GCP, Azure) and big data technologies is a plus.
• Skills:
  • SQL expertise for querying, analyzing, and validating large datasets.
  • Strong programming skills in Python, Java, or similar languages used for automation and data processing.
  • Experience with data monitoring and visualization tools (e.g., Tableau, Power BI, Looker, Grafana) to track and report on data quality.
  • Solid understanding of data governance principles, including data security, privacy, and compliance (GDPR, CCPA, etc.).
  • Strong problem-solving skills with the ability to troubleshoot data issues and devise effective solutions.
  • Excellent communication skills, with the ability to work cross-functionally and present technical concepts to non-technical stakeholders.
• Preferred:
  • Experience with CI/CD pipelines and automation tools (e.g., Jenkins, CircleCI) for integrating data quality checks.
  • Prior experience working with data science and analytics teams to ensure data readiness for machine learning and analytics use cases.
  • Experience in building scalable and reusable data quality processes in a SaaS environment.

What You’ll Get:

• Competitive compensation
• Unlimited paid time off policy
• Remote / Austin (we have get togethers on occasion in Austin so bonus if you’re a drive away)
• Competitive health insurance premiums (medical, dental & vision)
• A unique opportunity to revolutionize the sports and entertainment sponsorship industry
• Scale your career along with a fast growing organization that has significant growth opportunities
• The ability to work with a team of talented, fun, and hard-working colleagues in a highly collaborative culture