Technical Lead

Roles & Responsibilities

• Lead and define the QA strategy, test planning, and execution across complex data and application platforms.
• Design and implement automated testing frameworks using Python and PySpark for large-scale data validation.
• Validate data pipelines across Hadoop ecosystem (HDFS, Hive, Impala, Sqoop) ensuring completeness, accuracy, and consistency.
• Develop end-to-end test scenarios covering batch processing, data ingestion, transformation, and downstream consumption.
• Perform database validation and reconciliation using Oracle PL/SQL and SQL-based techniques.
• Validate machine learning pipelines and models, including experiment tracking via MLflow.
• Monitor and validate workflows orchestrated through Control-M / CA-7 schedulers.
• Collaborate with development teams to embed quality gates into CI/CD pipelines using Jenkins and Git.
• Drive test automation within DevOps pipelines, ensuring seamless integration with build and release processes.
• Perform Unix-based scripting for test automation, data checks, and batch validation.
• Lead defect triage, root cause analysis, and resolution tracking.
• Ensure adherence to regulatory and audit requirements, especially in data-sensitive environments.
• Mentor QA engineers and promote best practices in test automation and quality engineering.

Required Skills & Experience

• 8+ years of experience in Quality Assurance / Test Engineering, with leadership responsibilities.
• Strong proficiency in Python and PySpark 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.
• Strong Unix/Linux scripting experience.
• Experience integrating QA into CI/CD pipelines using Jenkins and Git.
• Familiarity with DevOps practices and automated pipeline testing.
• Experience with container platforms (Docker / OpenShift).
• Strong analytical and debugging skills, especially in data-related issues.

Nice-to-Have Skills

• Experience with Actimize or OFSAA FCCM platforms (financial crime / AML domain).
• Exposure to cloud platforms (AWS – Glue, Athena, S3, SageMaker).
• Experience testing machine learning models and data science workflows.
• Knowledge of data governance, lineage, and regulatory reporting frameworks.

Qualifications

• BACHELOR OF COMPUTER SCIENCE