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Data Quality Engineer (District of Columbia USA) at Jobgether. This position is posted by Jobgether on behalf of Inclusion Cloud. We are currently looking for a Data Quality Engineer in District of Columbia (USA).. Are you passionate about ensuring data integrity at scale? This role offers an exciting opportunity to design and implement automated data quality processes that directly impact internal operations and external customer experiences. You’ll work closely with cross-functional teams to validate and monitor large-scale datasets, write test plans, and continuously refine a robust data quality framework. With a strong focus on automation, communication, and problem-solving, this position is ideal for someone who thrives on delivering reliable, high-quality data across an organization.. . Accountabilities:. . Design, develop, document, and maintain a scalable data quality framework across data assets.. . Build automated and repeatable data quality checks to ensure accuracy and consistency.. . Validate data across pipelines and repositories against source systems.. . Collaborate with Data Engineering and other teams to gather requirements and align on test cases.. . Write and execute detailed test plans and document results for both technical and business audiences.. . Troubleshoot issues, perform root cause analysis, and fine-tune performance where necessary.. . Support ongoing data quality requests, tickets, and audits from stakeholders.. . Develop dashboards and reports to clearly communicate test results and data health metrics.. . . Bachelor's degree in Computer Science, Information Systems, or a related field — or 5+ years of equivalent professional experience.. . Strong analytical and critical thinking skills to resolve complex data issues.. . Solid foundation in development and automation, with a keen attention to detail and commitment to meeting deadlines.. . Proficient in SQL, capable of writing and reviewing complex queries.. . Programming experience with Python, Scala, or shell scripting; experience with Spark/PySpark is a strong asset.. . Familiarity with Hive (HQL), HDFS, and various data formats such as JSON, XML, ORC, Parquet, and AVRO.. . Proven ability to work independently while also collaborating effectively within a team.. . Excellent communication skills, especially when explaining technical details to non-technical stakeholders.. . Experience with performance tuning, debugging, and troubleshooting large-scale data processes.. . . Company Location: United States.