For one of our clients, a powerful financial risk management company, we are searching for a Lead Data Quality Analyst (technical).

The product is a Financial Asset Platform developed for the Commercial Real Estate industry

As a Lead Data Quality Analyst, you will play a critical role in analysing and managing Data Quality in Data Platforms or data-oriented software solutions at scale.

The role will be focused on improving existing or creating new Data Quality Analysis capability that enables the assessment of Data Quality in an automated manner and at scale within the Enterprise Data Platform.

You will report to the Engineering Manager of the Data Quality and Governance subdepartment and will manage the Data Quality team.

Responsibilities:

• Collaborate with Senior Data or Technology leadership to design new Enterprise Data Platform components and define implementation specifications.
• Establish and ensure adherence to Data Quality Analysis best practices for monitoring data quality at scale.
• Develop new features/components to enhance Data Quality Assessments using Python, SQL, and dbt.
• Involve and assist in generating sample input datasets for testing product features.
• Communicate Data Quality status, trends, and impact to business stakeholders and support related initiatives.
• Monitor Data Quality in client production environments and assist with Root Cause Analysis for failures.
• Certify product features for Data Quality across internal and client environments.
• Review and improve Data Quality components, identifying issues and creating improvement plans.
• Guide Data Quality Analysts on best practices and scalability.
• Collaborate with the Lead Software Engineer for Data Quality Automation (or Engineering Manager in their absence) to maintain infrastructure for scalable analysis.
• Foster a culture of ownership within the Data Quality Analysis team.
• Mentor junior Data Quality Analysts and design individual training plans.

Your contribution:

Your strong understanding of Data Platform architecture (Lambda, Kimball, Data Producers/Consumers, Data Contracts) and analytical skills will enable investors to make informed decisions. You'll work with internal teams to test new products while maintaining high data quality standards.

Key Qualifications:

• B.S. or M.S. in Statistics, Mathematics, Economics, Computer Science, Management Information Systems, or similar.
• Proficient Data Analysis skills using a mix of tools/frameworks such as SQL, Python stack (pandas, polars, scikit-learn, seaborn, great expectations, soda), Power BI/Tableau
• Strong database querying skills, ideally with SQL.
• Experience with REST APIs.
• Proven Software Engineering skills, preferably in Python for handling large datasets (retrieving, aggregating, profiling, generating test data).
• Familiar with version control (Git) and branching models like GitFlow.
• Knowledge of OOP, Design Patterns (e.g., Builder, Decorator) and SOLID principles (especially Single Responsibility and Dependency Inversion) are an advantage
• Experience with Snowflake, Docker is a plus.
• Experience with dbt, Dataform, Power BI (DAX), or Azure App Functions is a strong plus.

Only selected candidates will be contacted for further steps in the recruiting process.

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