Quality Engineer - Data

Techstra Solutions•Pittsburgh, PA

About The Position

We are seeking an experienced Lead Data Testing Engineer to support large-scale financial data platforms that power lending and credit operations. This role focuses on validating high-volume batch 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 financial services platforms.

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

Nice To Haves

Prior background as a software engineer or data engineer
Experience building custom data testing tools or frameworks
Exposure to machine learning, data profiling, or anomaly detection tools
Experience supporting regulatory reporting and data governance initiatives in banking
Relevant certifications in data engineering or quality assurance

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