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Quality Engineer

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: EXL
Full Time position
Listed on 2026-07-27
Job specializations:
  • IT/Tech
    Data Engineering, Data Analyst
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Our passion at EXL is enabling organizations to achieve a measurable, competitive advantage through Data Management. We partner with our clients to design and implement scalable, accessible, and innovative solutions. Our goal is to make sense of data to drive client’s business forward through data strategy, data governance and building cloud data platforms. EXL is a leading data analytics and digital operations and solutions company that partners with clients to improve business outcomes and unlock growth.

By bringing together deep domain expertise with robust data, powerful analytics, cloud, artificial intelligence (“AI”) and machine learning (“ML”), we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect.

Headquarters in New York, our team is over 44,500+ strong, with more than 50 offices spanning six continents.

Role Name:
Big Data Quality Engineer

Employment Type:

Full-Time Mode – Onsite Required Skills & Experience
  • 8+ years of experience in Quality Assurance / Test Engineering
    , with leadership responsibilities
  • Strong proficiency in Python and Py Spark for automation and data validation
  • Solid experience with big data platforms (Hadoop, Hive, Impala, Sqoop)
  • Hands‑on expertise in Oracle PL/SQL and relational database validation
  • Experience with workflow schedulers such as Control‑M or CA-7
  • Experience integrating QA into CI/CD pipelines using Jenkins and Git
  • Familiarity with Dev Ops practices and automated pipeline testing
  • Experience with container platforms (Docker / Open Shift)
  • Strong analytical and debugging skills, especially in data‑related issues
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