Data Testing Engineer (Lead)

Role Overview  The Lead Data Testing Engineer supports large-scale financial data platforms that power lending and credit operations.

This role focuses on validating high-volume batches and streaming data pipelines, ensuring data accuracy, integrity, and regulatory compliance across Hadoop-based ecosystems and Kafka-driven real-time data flows.

The ideal candidate brings deep expertise in data validation, automation, Agile delivery, and a strong passion for driving quality and innovation within the financial services platform.   Key Responsibilities  Design, develop, and execute data validation and testing strategies for large-scale financial datasets exceeding 5M+ customer records  Validate batch and streaming data pipelines, including Kafka, ETL / ELT processes, and Hadoop-based platforms spanning multiple technologies  Perform end-to-end testing of lending and credit data flows from source systems through downstream analytics and reporting layers  Build and maintain automated data testing frameworks for regression, reconciliation, and anomaly detection  Develop SQL-based and programmatic test scripts to validate data completeness, accuracy, timeliness, and data lineage  Partner with data engineers, developers, and business stakeholders to define data quality standards and acceptance criteria  Identify root causes of data defects and collaborate with teams on remediation strategies  Support regulatory, audit, and compliance requirements through strong data governance and documentation practices  Actively participate in Agile ceremonies, sprint planning, and continuous improvement initiatives  Champion innovation by introducing modern testing tools, automation practices, and monitoring solutions  Required Qualifications / Skills  5–10 years of experience in data testing, data quality, or analytics QA roles  Strong experience within financial services, preferably lending, credit, or risk platforms  Proven experience testing high-volume datasets (5M+ records)  Hands-on experience with :

• Hadoop ecosystem (Hive, HDFS, Spark, etc.)  Kafka or similar streaming platforms  Batch ETL / ELT pipelines  Relational and analytical databases  Advanced SQL skills for data validation and reconciliation  Experience with test automation frameworks and scripting languages (Python, Java, Scala, or similar)  Preferred Qualifications Preferred / Nice-to-Have Qualification Prior background as a software or data engineer.
• Experience building custom data testing tools or frameworks.
• Exposure to machine learning, data profiling, or anomaly detection tools.
• Experience with regulatory reporting and data governance in banking.

Certifications in data engineering or quality assurance Location :