Company Description
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com
Job Description
We are looking for a skilled Test Engineer with experience in automated testing, rollback testing, and continuous integration environments. You will be responsible for ensuring the quality and reliability of our software products through automated testing strategies and robust test frameworks
Design and execute end-to-end test strategies for data pipelines, ETL/ELT jobs, and database systems.
Validate data quality, completeness, transformation logic, and integrity across distributed data systems (e.g., Hadoop, Spark, Hive).
Develop Python-based automated test scripts to validate data flows, schema validations, and business rules.
Perform complex SQL queries to verify large datasets across staging and production environments.
Identify data issues and work closely with data engineers to resolve discrepancies.
Contribute to test data management, environment setup, and regression testing processes.
Work collaboratively with data engineers, business analysts, and QA leads to ensure accurate and timely data delivery.
Participate in sprint planning, reviews, and defect triaging as part of the Agile process.
Qualifications
4+ of experience in Data Testing, Big Data Testing, and/or Database Testing.
Strong programming skills in Python for automation and scripting.
Expertise in SQL for writing complex queries and validating large datasets.
Experience with Big Data technologies such as Hadoop, Hive, Spark, HDFS, Kafka (any combination is acceptable).
Hands-on experience with ETL/ELT testing and validating data transformations and pipelines.
Exposure to cloud data platforms like AWS (Glue, S3, Redshift), Azure (Data Lake, Synapse), or GCP is a plus.
Familiarity with test management and defect tracking tools like JIRA, TestRail, or Zephyr.
Experience with CI/CD pipelines and version control (e.g., Git) is an advantage.
