Lead Data Testing Engineer (Financial Services / Lending Platforms)

Techstra Solutions•Pittsburgh, PA

22h•Onsite

About The Position

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.

Requirements

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)
Strong understanding of data modeling, data warehousing, and lineage concepts
Experience working in Agile/Scrum environments
Excellent analytical, problem-solving, and communication skills
QA Testing (Mostly automation) 5-10 years
Lending product knowledge 2-3 years
Data lifecycle 5-10 years
Hadoop / Kafka - 4+ years
Agile Development Lifecycle –4 years

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