Data Quality Engineer

As a Data Quality Engineer at Excellent Pro Group, your primary responsibilities include designing and implementing effective data quality frameworks, monitoring data pipelines for integrity issues, and collaborating with engineering teams to resolve any data quality challenges. Your role is vital to ensure that our data systems remain accurate and reliable.

To apply for the Data Quality Engineer position at Excellent Pro Group, you should possess proven experience in data quality assurance and testing. Additionally, strong SQL skills and a solid understanding of data warehousing concepts are required to excel in this role.

The Data Quality Engineer is critical at Excellent Pro Group because they ensure the accuracy and reliability of data systems, which are the backbone of our data-driven operations. By maintaining high-quality data, you support informed decision-making and strategic initiatives within the company.

Essential skills for a Data Quality Engineer at Excellent Pro Group include strong analytical abilities, proficiency in SQL for data manipulation, a deep understanding of data quality processes, and excellent collaboration skills to work effectively with engineering teams.

While the Data Quality Engineer position at Excellent Pro Group is based in Seattle and Santa Monica, it is important to contact the team to discuss the possibility of remote work options, as flexible arrangements may be considered based on candidate qualifications and the nature of the work.

When answering this question, provide concrete examples of previous roles where you handled data quality assurance. Highlight specific frameworks you implemented and any tangible outcomes that resulted from your efforts, demonstrating how your experience aligns with the responsibilities of the Data Quality Engineer position.

Discuss specific tools you have used, such as Talend, Informatica, or custom scripts. Explain how you utilized these technologies for monitoring and ensuring data integrity, showcasing your versatility and technical knowledge as a Data Quality Engineer.

Detail your problem-solving methodology. Talk about identifying the source of the issue, collaborating with relevant teams to address the problem, and taking proactive measures to prevent reoccurrence, ensuring quality standards are consistently maintained.

Provide a specific example that illustrates your teamwork skills. Talk about the challenge, your role in facilitating effective communication, and how the collaboration resulted in a successful resolution, emphasizing the importance of teamwork in achieving high data quality.

Explain the steps you take when designing a data quality framework, including identifying key metrics, establishing quality thresholds, implementing monitoring processes, and ensuring continuous improvement. Outline how these practices apply to the Data Quality Engineer role.

Discuss your prioritization strategy, perhaps referencing urgency, potential impact on operations, and resource availability. Highlight your ability to stay organized and focused under pressure, a crucial trait for a successful Data Quality Engineer.

Prepare to describe specific SQL projects you've worked on, including querying, data transformation, and validation. Explain how mastering SQL aids in identifying data issues, improving data quality processes, and supporting your role as a Data Quality Engineer.

Mention any relevant resources you engage with, such as industry publications, webinars, or professional networks. Emphasize your commitment to continual education and staying at the forefront of data quality standards and innovations.

Share a specific project experience where your actions took a data quality initiative from conception to execution. Highlight the challenges faced, the strategies employed to overcome them, and the measurable improvements achieved in data quality as a direct result of your efforts.

Share your insights on trends such as automation, AI integration, and the increasing importance of data governance. Discuss how these advancements will shape the role of data quality professionals in organizations and how you plan to stay relevant in these evolving dynamics.