Hybrid Data Quality Automation Engineer (Finance)

Morningstar Credit Ratings, LLC; Hinoba-an; Hybrid; PHP 5,643,000 - 8,777,000; Full time

Job summary

Morningstar Credit Ratings, LLC is seeking a Data Quality Automation Engineer to design and implement scalable data quality controls across enterprise-scale platforms. You'll build validation frameworks and monitoring to ensure data integrity for investment research workflows.

The role requires advanced Python and PySpark experience, strong SQL, and hands-on data quality engineering in a financial data environment. Hybrid work arrangements are offered.

Qualifications

• Advanced Python development.
• Strong SQL and data analysis skills.
• Hands-on PySpark and distributed data processing.
• Experience building automated data validation & reconciliation frameworks.
• Experience with large-scale financial datasets and data profiling.

Responsibilities

• Design, build, and maintain automated data quality frameworks across enterprise-scale data platforms.
• Develop validation and reconciliation capabilities for multi-asset financial datasets.
• Implement monitoring to identify anomalies, outliers, and data gaps.
• Collaborate with Data Engineering to embed quality controls in ETL/ELT pipelines.
• Support onboarding and validation for new datasets used in investment workflows.
• Validate data from providers like Bloomberg, FactSet, Morningstar, LSEG.

Skills

Python

SQL

PySpark

Data quality

Education

Bachelor's or Master's in quantitative/engineering

Tools

Great Expectations

AWS

Deequ

Job description

Morningstar Credit Ratings, LLC is seeking a Data Quality Automation Engineer to design and implement scalable data quality controls across enterprise-scale platforms. You'll build validation frameworks and monitoring to ensure data integrity for investment research workflows.

The role requires advanced Python and PySpark experience, strong SQL, and hands-on data quality engineering in a financial data environment. Hybrid work arrangements are offered.