Data Quality Engineer (Global Markets), Citi

Citi

Location:
India, Pune

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

As a Data Quality Engineer in the Global Markets division of a leading investment bank, you will ensure the integrity, accuracy, and consistency of data across critical trading, risk, and compliance systems. Your work will directly impact the bank’s ability to execute trades effectively, manage risk efficiently, and comply with financial regulations globally.

Job Responsibility:

Develop and implement automated data quality checks for real-time and batch trading data
Monitor and validate data pipelines for trade execution, pricing models, risk analytics, and post-trade settlement
Work with trading desks, quants, and data engineers to identify and resolve data anomalies
Build data profiling, lineage tracking, and metadata management solutions to ensure traceability and compliance
Integrate data validation rules into CI/CD pipelines, ensuring continuous data reliability in trading applications
Conduct root cause analysis for data quality issues and drive corrective actions
Ensure compliance with global financial regulations, including Basel III & FRTB (Risk & Capital Requirements), MiFID II & EMIR (European Trading & Reporting Standards), Dodd-Frank & CCAR (US Regulations)
Collaborate with DevOps and Cloud teams to optimize data quality solutions in cloud-based environments (AWS, Azure, GCP)
Leverage AI/ML-based anomaly detection models to proactively detect data inconsistencies

Requirements:

At least 5 years of experience in Data Quality Engineering, Data Governance, or Data Testing within a global banking or capital markets environment
Strong understanding of trading data structures, market data, and financial instruments across asset classes (Equities, Fixed Income, FX, Derivatives, Commodities)
Knowledge of risk metrics and trade lifecycle processes in investment banking
Experience with financial market data providers such as Bloomberg, Reuters, and ICE
Proficiency in SQL for data validation and querying large datasets
Hands-on experience with Python or Java for data quality automation
Experience with data quality tools such as Great Expectations, Monte Carlo, Talend, Collibra, or Informatica DQ
Exposure to big data platforms such as Snowflake, Databricks, Spark, and Hadoop
Experience with data pipeline orchestration tools such as Airflow, DBT, or Prefect
Experience embedding data quality tests in DevOps CI/CD pipelines
Experience working with cloud data services on AWS, Azure, or GCP
Strong analytical and troubleshooting skills for debugging data quality issues
Ability to work in a fast-paced trading environment with cross-functional teams

Nice to have:

Experience with real-time market data validation and anomaly detection
Knowledge of regulatory reporting standards such as BCBS 239, Volcker Rule, and IFRS 9
Exposure to data observability tools like Datafold, Soda, or Bigeye
Experience with Kafka, Kinesis, or other real-time streaming technologies for market data validation

What we offer:

Work on high-impact financial data pipelines powering global trading operations
Collaborate with top-tier engineers, quants, and traders in a cutting-edge financial environment
Gain exposure to AI-driven data validation and anomaly detection in real-time markets
Be part of a global financial institution with opportunities for career growth and leadership development

Additional Information:

Job Posted:
March 22, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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Data Quality Engineer (Global Markets)