Quality Engineering Lead – Data & Reporting Platforms

2. Data Virtualization & Federation Testing

3. AI & Conversational Intelligence Testing

4. Big Data & Reporting Platform Testing

5. CI/CD & Test Automation Engineering

Required Technical Skillsets

• 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 integrating automated data test suites into enterprise CI/CD pipelines (e.g., Jenkins, Tekton, GitLab CI) to enable continuous testing.
• Test Methodologies: Deep understanding of Agile/Scrum methodologies, functional, integration, regression, and parallel-run testing for large-scale migrations.

Preferred / Nice-to-Have Skillsets

• Modern Lakehouse & Warehouse Platforms: Familiarity with cloud-native data platforms, such as Databricks or Snowflake (experience with Google BigQuery is also valued).
• Distributed Data Processing Engines: Familiarity with distributed compute engines, specifically Apache Spark (PySpark, Spark SQL) or Apache Flink for large-scale data processing.
• Data Quality Automation: Experience implementing automated data quality frameworks using industry-standard tools such as Great Expectations , dbt test , Soda / SodaCL , or Deequ / PyDeequ .
• AI/ML & NLP Testing: Experience testing LLM-backed applications, validating Natural Language-to-SQL engines (e.g., conversational query interfaces), prompt validation, and autonomous agent testing.

Leadership & Methodology

Experience & Qualifications

• Total Testing Experience: Minimum 10-12 years of relevant experience in software testing, quality engineering, or data engineering.
• Data Automation Experience: Minimum 5-8 years of hands-on experience in automated data testing, ETL testing, or data pipeline quality engineering.
• BI & Analytics Verification: Minimum 5-8 years of experience in report/BI testing, data reconciliation, and source-to-target data validation.
• Education: Bachelor’s degree in Computer Science, Information Systems, or equivalent engineering field.
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Most Relevant Skills

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Other Relevant Skills

• Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
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