Data Quality Engineer

Design and implement data quality rules in Informatica Data Quality (IDQ) to validate file formats, schema consistency, completeness, and business logic compliance.

• Establish and manage SLA monitoring frameworks to track external file delivery timeliness, frequency, and compliance with contractual or operational expectations.

• Create and maintain alerting and exception workflows for missing, late, or malformed file deliveries.

• Profile incoming data stored in Azure Blob Storage and loaded into Snowflake for issues such as null values, duplicates, schema drift, or logic violations.

• Work with data engineering teams to ensure seamless integration of validation steps into SWIB’s ingestion pipelines.

• Collaborate with business and governance stakeholders to define quality thresholds, acceptance criteria, and reporting standards.

• Generate documentation, dashboards, and issue logs to track quality metrics and SLA performance.

• Contribute to root-cause analysis and implement corrective actions to address quality breaches or SLA violations. The Contractor requires the following skills, abilities, and background:

• 3+ years of advanced experience with Informatica Data Quality (IDQ), including rule creation, data profiling, and monitoring.

• Familiarity with financial datasets, including security master and holding datasets, commonly used in investment operations.

• Execution level familiarity with ETL orchestration, data contracts, or third-party file delivery standards.

• Proficiency in Snowflake and experience with profiling and managing large datasets.

• 3+ years of experience working with Azure Blob Storage and Snowflake Snowpipe.

• 2+ years of experience working with FactSet.

• 2+ years of experience designing and supporting SLA monitoring and alerting systems around data intake.

• 3+ years of familiarity with data quality dimensions (e.g., accuracy, completeness, validity, timeliness)