Description:
This is a data quality role built for your skills. We are hiring a Data Quality Engineer to apply fundamental data engineering concepts and build scalable systems, automate pipelines, and ensure reliability in addressing the critical challenge of data integrity.
Your Mission:
Architect and own the frameworks that guarantee the accuracy and trustworthiness of our core data assets. You will build the systems that prevent data issues, moving beyond manual checks to engineered solutions.
Key Responsibilities:
- Design, build, and maintain automated data quality frameworks integrated directly into our data pipelines.
- Develop and execute strong Python scripts for data validation to proactively identify and resolve data inconsistencies.
- Monitor data health and track quality metrics (completeness, uniqueness, and timeliness) using the ELK Stack (Elasticsearch, Logstash, and Kibana).
- Diagnose root causes of data issues in collaboration with other data engineers and implement permanent corrective solutions.
- Document all data quality processes, findings, and standards to ensure clarity and compliance.
- Identify and drive improvements in our data quality procedures, tools, and automation.
What You Bring to the Table:
- A Bachelor's or Master’s degree in Data Science, Computer Science, IT or a related field.
- Proven experience in a Data Engineering or Data Quality Engineer role.
- Strong programming skills in Python for data validation and automation
- Expert, hands-on proficiency with the ELK Stack (Elasticsearch, Logstash, Kibana).
- A solid understanding of data profiling, metric definition, and root cause analysis.
- A disciplined approach to following our SOPs and handling sensitive/confidential data.
- Practical experience with project management tools like Trello.