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Applaudo is seeking a Data Quality Assurance Engineer (3-month contractor) to ensure data accuracy across large-scale environments. You will validate ETL processes, write SQL queries, and test data across back-end systems and data platforms.
The role emphasizes collaboration with technical teams to resolve defects and improve testing practices. Qualified candidates have 1+ years in data quality testing, strong English, and experience with Airflow, Jira, ALM, and data profiling in high-volume
You are a Data Quality Assurance Engineer who enjoys ensuring the accuracy, completeness, and reliability of data across complex data environments. You have hands‑on experience validating high-volume datasets, testing ETL processes, and using SQL to identify data inconsistencies and verify expected results.
You are analytical, detail‑oriented, and comfortable working across databases, Big Data environments, and backend systems. You bring a strong quality mindset to data‑driven solutions and enjoy collaborating with technical teams to identify defects, validate data integrity, and continuously improve testing practices.
Note: This role operates under a 3-month contractor model.
We Are Engineered Different.
At Applaudo, talented people design, build, and scale meaningful, AI‑powered solutions that create real business impact. As an AI‑native organization, we collaborate across design, development, cloud, data, and artificial intelligence to turn ideas into scalable products that transform how companies operate, make decisions, and grow.
We are building a high‑performance culture grounded in five values: Empowering Excellence, Collaborative Teamwork, Unsolicited Respect, Consistent Transparency, and Efficient Communication. These define how we work, how we support one another, and how we hold ourselves accountable.
Applaudo is a place for people who want to learn fast, take ownership, and work alongside strong teams they are proud to belong to. Joining us means being part of an organization that is evolving intentionally, investing in modern ways of working, and leading AI‑native transformation at scale.