Data Quality Analyst

The Data Quality Analyst will collaborate with TCW’s Data Engineering team to strengthen data integrity across essential enterprise platforms. The position will be responsible for creating, deploying, and overseeing data quality rules, with a preference for leveraging Ataccama DQ, to ensure TCW’s data assets align with required standards for accuracy, completeness, consistency, and timeliness. This analyst will also work closely with data engineers, business analysts, and governance teams to resolve data defects and incorporate quality validations into data pipelines.

Key Responsibilities

• Design, build, and maintain data quality rules within Ataccama DQ (required).
• Convert business data quality requirements into technical rule logic.
• Parameterize rules to enable scalability and reusability.
• Conduct dataset profiling to identify anomalies, missing values, duplicates, and inconsistencies.
• Create reports that surface data quality gaps and suggest remediation actions.
• Configure dashboards and alerts to monitor rule performance and compliance over time.
• Partner with Data Engineering to integrate rules into ETL/ELT pipelines.
• Analyze and troubleshoot failed data quality checks and coordinate with upstream/downstream teams to resolve issues.
• Document data defects, root causes, and resolution approaches.
• Work with Data Governance and Business SMEs to establish data standards and stewardship processes.
• Support metadata documentation and data lineage tracking. 

Required Skills & Experience

• 5+ years of experience in data quality, data management, or data engineering roles.
• Strong experience with data quality tools (Ataccama required).
• Proficiency in SQL for rule creation, data profiling, and validation.
• Experience with ETL/ELT workflows and modern data platforms (Snowflake, Databricks, Azure preferred).
• Knowledge of data governance frameworks and best practices.
• Strong problem-solving, analytical, and communication skills. 

Preferred Skills

• Previous experience in asset management or financial services data environments.
• Knowledge of reference data, market data, and client data domains.
• Experience automating DQ workflows using Python, Spark, or other scripting languages.
• Experience with cloud-based architectures (Azure, AWS).

Deliverables / Success Metrics

• Deliver baseline data quality rules across prioritized datasets (e.g., client, security master, transaction data).
• Provide monthly reporting on rule performance, exceptions, and remediation status.
• Maintain a documented library of data quality checks mapped to business requirements.
• Show measurable reduction in recurring data quality issues and improved SLA adherence for downstream consumers.