Data Quality Specialist

This role will support a key project by performing data quality and validation activities to ensure the integrity, accuracy, and completeness of data across SDLH and our Data Repository.

Location: 100% ON-SITE, Asuncion-Paraguay . Working hours are based on the US Central Time Zone.

About the Company :

Abstra is a fast-growing, Nearshore Tech Talent services company, providing top Latin American tech talent to U.S. companies and beyond. Founded by U.S.-bred engineers with over 15 years of experience, Abstra specializes in sourcing skilled professionals across a wide range of technologies to meet our clients’ needs, driving innovation and efficiency.

Key Responsibilities :

Design and execute source (SDLH silver to gold) and source-to-target (SDLH gold to Data Repository gold) validation .

Develop and run SQL scripts/queries to compare record counts, field-level values, and aggregates between source and target datasets.

Identify , document, and track data discrepancies, mapping errors, or transformation issues.

Collaborate with data engineers to implement QA rules and validation checks within the Great Expectations framework.

Collaborate with the data team to define validation rules and acceptance criteria.

Build reusable QA/reconciliation frameworks or test scripts to support repeatable testing across migration phases

Support UAT (user acceptance testing) of the converted reports.

Document data quality findings, root causes, and remediation recommendations.

Requirements :

Familiarity with core financial system concepts.

Advanced SQL proficiency , specifically: T-SQL – working with SQL Server-based systems for extraction, transformation, and validation logic. Databricks SQL – querying and validating data within lakehouse/big data environments.

Data profiling and anomaly detection.

Familiarity with data quality and validation frameworks , such as Great Expectations , for defining, automating, and enforcing data quality checks

Familiarity with ETL/ELT pipelines and data migration methodologies , especially medallion architecture.

Desired Skills and Experience:

Prior hands-on experience in data migration QA, ideally within financial/accounting systems .

Experience building or executing structured source-to-target reconciliation processes.

Hands-on experience with data quality frameworks (e. g., Great Expectations, dbt tests, or similar) for automating validation rules.

Comfort working independently with clear deliverables.

What We Offer:

Competitive compensation paid in USD.

20 days of paid time off (PTO) per year.

Opportunities for professional growth and career development.

Company-provided equipment.

A collaborative, inclusive, and multicultural work environment.

The opportunity to contribute to meaningful projects alongside a talented and supportive team.

• Pre-Employment Verification
• As part of our standard onboarding process, candidates who successfully complete the interview process and accept an employment offer will be required to complete an employment verification check, and background check. This process will confirm job titles and dates of employment with two previous employers and is a standard requirement for all new employees joining the company.