Data Quality Engineer – Operational Platform
| Company | Focus Financial Partners |
|---|---|
| Location | St. Louis, MO, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Junior |
Requirements
- Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent work experience.
- Strong understanding of data quality methodologies, tools, and processes.
- Hands-on experience with SQL and data querying for validation and testing.
- Familiarity with ETL processes, data pipelines, and data warehousing concepts.
- Experience in scripting and test automation using tools such as Python, Java, or other relevant technologies.
- Knowledge of CI/CD pipelines and tools such as Jenkins or GitLab.
- Familiarity with tools like dbt and Great Expectations for data testing and validation.
- Knowledge of data visualization tools (e.g., Tableau, Power BI) and their role in validating data outputs.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
Responsibilities
- Collaborate with the Data Engineering team to understand requirements, design specifications, and technical implementations.
- Develop and execute test plans, test cases, and test scripts for ETL processes, data pipelines, and data transformation workflows.
- Perform end-to-end testing of data platforms to ensure accuracy, reliability, and scalability.
- Validate data integrity across multiple systems and environments.
- Identify, document, and track defects, working with the engineering team to resolve issues in a timely manner.
- Automate testing processes for data validation and system performance to improve efficiency.
- Implement testing and validation using tools such as dbt and Great Expectations.
- Monitor data quality and identify opportunities for improving test coverage.
- Validate APIs and RESTful services to ensure proper integration and data flow between systems.
- Provide regular updates on testing progress, issues, and risks to the team and stakeholders.
- Stay up-to-date with industry best practices and new tools for data testing and quality assurance.
Preferred Qualifications
- Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure, GCP).
- Familiarity with CI/CD pipelines and tools such as Jenkins or GitLab.
- Knowledge of data governance and data security best practices.
- Experience testing APIs and RESTful services for integration and functionality validation.