Testing Senior Group Manager

Citi • Rutherford, NJ

2d • Hybrid

About The Position

Citibank, N.A. seeks a Testing Senior Group Manager for its Rutherford, New Jersey location. This role involves determining and implementing testing strategies, structuring the testing group for maximum impact and resource efficiency, and analyzing business requirements to create functional test cases. The position requires using Python, Java, and SQL for automation testing and building enterprise data quality engineering platforms, establishing controls and data standards, and designing technical solutions using Big Data technologies. The manager will conduct architectural design reviews, lead data quality engineering teams, evaluate data quality and accuracy, and drive innovative testing strategies. This role also involves influencing IT testing through planning, budget management, policy setting, and ensuring IT organizations meet business strategy and goals. Responsibilities include overseeing the aggregation and reconciliation of data sets across multiple ETL pipelines and leading the exploration of data anomaly detection using machine learning and AI.

Requirements

• Requires a Bachelor’s degree or foreign equivalent in Engineering (any), Computer Science, Information Technology or related field and 8 years of progressive post-baccalaureate experience as a Team Lead, Manager, Software Engineer, Analyst, Programmer Analyst, QA Engineer, AVP, Associate or related position involving test automation strategy and developing test automation framework.
• 7 years of experience must include: Evaluating data quality and accuracy
• 7 years of experience must include: Aggregation and reconciliation of data sets across multiple ETL pipelines using SQL and Excel
• 7 years of experience must include: Python, Java and SQL for automation testing and building enterprise data quality engineering platforms
• 7 years of experience must include: Establish controls and data standards on enterprise data platform
• 7 years of experience must include: Hive, Impala, Apache Spark, Oracle, Relational Database system
• 7 years of experience must include: Determining, implementing and executing testing strategy of ETL software applications
• 7 years of experience must include: Impact analysis and defining functional validations for feature development and enhancements on Enterprise Data Platforms
• 7 years of experience must include: Hadoop, KDB, financial Institution data platforms and data sets.

Responsibilities

• Determine the approach to implement testing strategies and execute testing strategies.
• Structure the testing group to ensure the greatest impact, efficient use of resources, and alignment to business structures.
• Analyze business requirements from stakeholders and prepare functional test cases including the impact analysis to the current state application.
• Use Python, Java and SQL for automation testing and building enterprise data quality engineering platforms.
• Establish controls and data standards on enterprise data platform.
• Design and document technical solutions using Big Data stack of technologies, including aggregation and reconciliation of data sets across multiple ETL pipelines using SQL and Excel.
• Conduct architectural design reviews for automation testing, and lead data quality engineering teams to build enterprise data quality engine for regulatory, liquidity, and risk reporting testing.
• Evaluate data quality and accuracy and address complex issues using Hive, Impala, Apache Spark, Oracle, Relational Database system, Hadoop, KDB, and financial institution data platforms and data sets.
• Drive innovative testing strategies that support technological changes.
• Influence IT testing through planning, finances and budget, end results, and setting policies.
• Exercise control over resources, budget, policy formulation and planning.
• Ensure that the IT organization is defining and implementing testing and control plans to meet business strategy and goals.
• Oversee the initiatives of aggregation and reconciliation of data sets across multiple extract transform load pipelines in order to determine monetary data accuracy using various data analysis tools and technologies including SQL, Excel, and build tools.
• Lead the exploration of data anomaly detection controls using machine learning and artificial intelligence and automated data quality engine.

Benefits

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Number of Employees: 5,001-10,000 employees