Data Engineer Specialist, Data Quality

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Act as the primary technical authority for Data Quality, establishing standards, frameworks, processes, and best practices for both analytical and operational data.

• Develop, implement, and continuously enhance automated data quality controls throughout the lifecycle of data products.

• Spearhead Data Quality initiatives in collaboration with Data Engineering, Data Governance, and business teams.

• Establish and execute data quality metrics, rules, SLAs, scorecards, and monitoring systems.

• Integrate Data Quality practices with DataOps, observability, CI/CD, and data governance capabilities.

• Assist in the implementation and advancement of Data Catalog, Data Lineage, Metadata Management, and data product certification processes.

• Analyze root causes of quality issues, leading corrective and preventive measures with the relevant teams.

• Aid in defining and adopting standards for Data Products and Enterprise Data Domains, ensuring data consistency and reliability.

• Serve as a technical mentor for engineers and analysts, sharing expertise and promoting the organization’s Data Quality maturity.

• Influence roadmaps and technical choices regarding data quality, reliability, and governance.

⛳️ Requirements

• Bachelor’s degree or an equivalent higher education qualification.

• Extensive experience in Data Engineering within large-scale enterprise analytics settings.

• Demonstrated experience in implementing Data Quality initiatives, including the establishment of rules, controls, monitoring, and remediation processes.

• In-depth knowledge of Data Quality Frameworks, Data Profiling, Data Validation, Data Cleansing, and Data Observability.

• Familiarity with analytical platforms such as Databricks, Snowflake, or similar technologies.

• Experience in developing data pipelines using SQL, Python, and contemporary Data Engineering tools.

• Understanding of Great Expectations and dbt for Data Quality, along with concepts related to lineage, governance, privacy, retention, and anonymization.

• Knowledge of DataOps, CI/CD, version control, and automated testing for data.

• Familiarity with Data Catalog, Data Lineage, Metadata Management, Data Stewardship, and Data Governance.

• Experience with Data Products, Data Domains, or domain-oriented architecture models.

• Ability to act as a technical authority, influence architectural decisions, and facilitate discussions with local and global teams.

• Advanced English proficiency for effective communication in international contexts.

🏝️ Benefits

• Remote work