Data Quality Automation Engineer | Databricks & IAM

Coforge; México; Presencial; MXN 650.000 - 900.000; Jornada completa

Descripción de la vacante

Coforge is seeking a Data Quality Engineer in Mexico to ensure data accuracy, completeness, consistency, and reliability across enterprise datasets.

The role focuses on building automated data quality frameworks using SQL, Python, and PySpark, with exposure to data governance and IAM processes. Collaboration with data owners and engineers is essential to define quality requirements and drive remediation.

Formación

• Strong experience in Data Quality Engineering, Data Validation, or Data Quality Management.
• Advanced SQL skills, including complex joins, CTEs, window functions, aggregations, and large-scale data validation.
• Strong Python programming skills for data validation, automation, exception handling, and reusable framework development.
• Experience building automated data quality checks, monitoring solutions, and validation frameworks.
• Hands-on experience with Databricks, PySpark, Delta Lake, or similar data processing technologies.
• Understanding of ETL/ELT processes, data pipelines, data transformations, and data integration.
• Knowledge of data quality dimensions, including accuracy, completeness, consistency, validity, uniqueness, and timeliness.
• Experience defining data quality KPIs, thresholds, controls, and remediation processes.
• Strong analytical, problem-solving, communication, and stakeholder management skills.

Responsabilidades

• Design, implement, and maintain data quality rules, validation frameworks, controls, thresholds, and KPIs.
• Develop complex SQL queries for data profiling, reconciliation, source-to-target validation, and exception identification.
• Build scalable data quality automation solutions using Python, SQL, and PySpark.
• Implement automated checks, exception handling, alerting, reporting, and remediation tracking.
• Work with Databricks, Delta Lake, and data pipelines to implement data quality.
• Monitor data quality metrics, identify trends, and collaborate with stakeholders to drive resolution.
• Support data governance practices, including data ownership, stewardship, metadata management, and quality standards.
• Collaborate with Data Owners, Data Stewards, Data Engineering, and business teams to define and enforce data quality requirements.
• Support data access governance initiatives, including access reviews, entitlement management, provisioning workflows, and audit evidence.
• Where applicable, automate access management processes and integrations using Python, REST APIs, and workflow tools.

Conocimientos

Data Quality Engineering

Data Validation

Data Quality Automation

SQL

Python

Databricks

PySpark

Delta Lake

Data Governance

IAM

RBAC/ABAC

REST APIs

Jira

Streamlit

Herramientas

Databricks

Delta Lake

Jira

REST APIs

Streamlit

Descripción del empleo

Coforge is seeking a Data Quality Engineer in Mexico to ensure data accuracy, completeness, consistency, and reliability across enterprise datasets.

The role focuses on building automated data quality frameworks using SQL, Python, and PySpark, with exposure to data governance and IAM processes. Collaboration with data owners and engineers is essential to define quality requirements and drive remediation.