Mid-Level Data Quality

Job Description:

We are seeking a detail-oriented Mid-Level Data Analyst to support enterprise Data Quality initiatives within a Financial Services or Capital Markets environment. This role will focus on monitoring, validating, and improving the integrity, completeness, and accuracy of critical financial, trading, and regulatory data. The ideal candidate will have experience working with complex datasets across trading, risk, finance, or operations domains and a strong understanding of data governance and regulatory reporting requirements.

Key Responsibilities

Analyze and validate large financial datasets to ensure accuracy, completeness, and consistency across trading, risk, and finance systems.

Develop and execute data quality rules, controls, and monitoring processes across structured and semi-structured data environments.

Perform root cause analysis on data discrepancies and partner with technology and business teams to implement remediation plans.

Support regulatory reporting data validation (e.g., trade reporting, market risk, liquidity reporting, CCAR, Basel, or similar frameworks).

Design and maintain data quality dashboards and metrics to track trends, exceptions, and remediation progress.

Partner with Data Governance teams to support data lineage, metadata management, and data ownership initiatives.

Work closely with front office, middle office, risk, finance, and operations stakeholders to ensure alignment of data definitions and business rules.

Support reconciliation processes between upstream trading platforms and downstream reporting systems.

Document data definitions, transformation logic, and validation procedures.

Assist in audit and compliance reviews related to data quality and reporting controls.

Required Qualifications

3–7 years of experience as a Data Analyst within Financial Services or Capital Markets.

Strong understanding of financial instruments (equities, fixed income, derivatives, FX) and related trade lifecycle processes.

Experience performing data profiling, reconciliation, and root cause analysis.

Proficiency in SQL and experience querying large relational databases.

Experience with data visualization tools (Power BI, Tableau, or similar).

Strong understanding of data governance, data quality frameworks, and control environments.

Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with regulatory reporting frameworks (Basel III, CCAR, MiFID, Dodd-Frank, EMIR).

• Familiarity with data management tools (Informatica, Collibra, Alation, Talend).

• Knowledge of risk systems, trading platforms, or market data feeds.

• Python or R experience for data analysis and automation.

• Experience working in Agile environments.

• Key Competencies

• Strong attention to detail and data accuracy

• Ability to work with large, complex datasets

• Effective cross-functional collaboration

• Strong documentation and governance discipline

• Ability to prioritize in fast-paced, deadline-driven environments