Quality Engineering Lead - Data & Reporting Platforms

Citigroup; Pune District; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

Citigroup seeks a VP, Quality Engineering Lead to define, build, and drive automated data and report testing across a next-gen AI-powered analytics ecosystem. You will lead a team of QE engineers, setting standards and driving continuous improvement in data validation, virtualization, and AI query interfaces.

You will architect end-to-end test strategies for data federation, schema validation, access controls, and BI/dashboard verification while partnering with engineering and product teams to

Responsabilidades

• Architect and execute a comprehensive data and reporting automated testing strategy.
• Lead a team of Data & Report Quality Engineers and drive QE maturity.
• Define testing standards, automated gates, and data verification protocols.
• Own quality metrics reporting to senior global tech leaders.
• Develop automated testing for data virtualization, federation, and AI interfaces.
• Validate query execution latency and data integrity across federated engines.
• Design security tests for data governance and masking.
• Test BI/report verification during large-scale migrations.

Conocimientos

Data & Report QE Leadership

Data Virtualization Testing

Federation Testing

NLP/Conversational AI Testing

Automation Frameworks

CI/CD Integration

Python/Java

Security Testing

SQL Testing

Herramientas

Starburst Trino

Denodo

Dremio

AWS Athena

Tableau

Jenkins

GitLab

Postman

Descripción del empleo

Role Overview

We are seeking a highly skilled and experienced VP, Quality Engineering Lead to define, build, and drive our automated data and report testing strategy. In this role, you will lead the Quality Engineering (QE) initiatives for our next-generation, AI-powered data and reporting ecosystem.

As a hands-on leader, you will design robust automated test suites to validate complex data architectures-specifically focusing on data virtualization, massive data federation, data contract testing, and the verification of emerging natural language/conversational AI query interfaces. You will manage a talented team of quality engineers, establish testing standards, and collaborate closely with engineering, and product teams to ensure high-quality, secure, and performant data and report delivery.

Key Responsibilities

• Test Strategy & Quality Leadership
  • Data & Reporting Test Strategy: Architect and execute a comprehensive, end-to-end automated testing strategy covering data virtualization, federated queries, BI/reporting, and AI-enabled analytical interfaces.
  • Team Leadership: Lead, mentor, and functionally manage a specialized team of Data & Report Quality Engineers, fostering a culture of modern Quality Engineering (QE) and continuous improvement.
  • Governance & Compliance: Define operating standards, automated quality gates, and data verification protocols across the analytics and reporting delivery lifecycle.
  • Stakeholder Management: Own the reporting of quality metrics, pipeline coverage, and test automation maturity to senior global technology and engineering leaders.
• Data Virtualization & Federation Testing
  • Federated Query & Virtualization Validation: Develop automated testing frameworks to validate query execution, latency, and data integrity across massive federated query engines and data virtualization platforms (e.g., Starburst, Trino, Presto, Denodo, Dremio, AWS Athena, or Apache Drill ) connecting dozens of heterogeneous catalogs without physical data movement.
  • Data Contract & Schema Validation: Implement automated schema validation and data contract testing to ensure curated, virtualized data products strictly adhere to published business definitions and system requirements.
  • Access Control & Security Testing: Design data-driven security tests to verify that centralized data access governance (e.g., Apache Ranger, role/attribute-based access controls) and data masking are flawlessly applied.
• AI & Conversational Intelligence Testing
  • Natural Language Query Testing: Establish frameworks to test conversational AI interfaces that allow users to query data using natural language. Validate natural language processing (NLP) models, intent recognition, NLP-to-SQL translation logic, and the accuracy of the underlying datasets returned.
  • Autonomous Agent Verification: Design testing patterns for non-deterministic AI agents (e.g., automated alerting systems and contextual research assistants), validating logical outputs, threshold actions, and boundary limits.
• Big Data & Reporting Platform Testing
  • Report & Dashboard Verification: Devise automated strategies to test visual correctness, performance, and backend data reconciliation for BI platforms (e.g., Tableau, custom web-based dashboards) during large-scale migration phases of legacy systems (comprising hundreds of reports).
  • Data Lakehouse & Pipeline Testing: Lead automation efforts validating complex data pipelines across hybrid databases (Oracle, SQL Server) and modern analytical lakehouses.
  • Data Reconciliation: Design and automate source-to-target data reconciliation, schema drift detection, and data lineage validation to ensure reports match underlying source systems perfectly.
• CI/CD & Test Automation Engineering
  • Continuous Quality Pipelines: Seamlessly integrate data and report automation suites into enterprise CI/CD pipelines (Jenkins, Tekton, GitLab, etc.) to trigger continuous verification with each deployment code path.
  • Triage & Defect Management: Champion structured defect triage, prioritizations, and root cause analysis across complex, multi-tiered data and reporting infrastructure environments.

Technology Skills

• Data Virtualization & Federation: Hands-on experience with enterprise data virtualization or query federation platforms, such as Starburst, Trino, Presto, Denodo, Dremio, AWS Athena, or Apache Drill .
• BI & Reporting Platforms: Deep expertise in testing BI and reporting platforms (e.g., Tableau, custom web-based dashboards, Aspose, or similar reporting engines).
• Database Querying & Testing: Advanced SQL expertise with hands-on experience testing relational databases (Oracle, SQL Server) and NoSQL databases.
• Programming Languages: Proficiency in Python or Java to build, maintain, and scale custom test automation frameworks.
• API Testing: Strong experience with API testing (REST/SOAP) and data contract validation using tools like Postman, RestAssured, or custom scripts.
• CI/CD Integration: Experience integ