Data Quality Engineer (Data QA)

Description

Job Summary: We are seeking a Data Quality Engineer to ensure data quality, reliability, and consistency on the platform, validating pipelines and preventing errors. Key Highlights: 1. Ensure data quality and reliability on the platform. 2. Validate data pipelines and identify inconsistencies. 3. Collaborate with Data Engineering to prevent errors and improve quality. **Description:** ---------------- Do you have experience as a **Data Quality Engineer**, validating data pipelines and ensuring information quality? Are you looking for your next professional challenge? If so, this opportunity may be for you! **Did you know us?** In 2025, myCloudDoor and Henson Group merged to form ALIANDO, a global company born from the strategic fusion of two leading Cloud solution providers. This integration positions us as a Leading Partner in Cloud innovation, Artificial Intelligence, and Managed Services, with a clear focus on supporting organizations through their digital transformation: Cloud Infrastructure & Modernization | FinOps | Data & AI | Cybersecurity | SAP on Azure | Business Applications: Power Platform, Dynamics 365, low-code/no-code solutions | Managed Services & Licensing. With presence across North America, Europe, the Middle East, and LATAM—and a global team of experts—we lead high-impact projects built on technologies such as Azure OpenAI, Copilot, and SAP. If you seek growth within an international, innovative, and continuously evolving environment, ALIANDO is your place. We are looking for a **Data Quality Engineer** responsible for ensuring **data quality, reliability**, and **consistency** within the data platform. This role is critical to guaranteeing that processed and consumed data meets defined standards and adequately supports business requirements. The candidate will be responsible for validating **data pipelines**, identifying inconsistencies, and closely collaborating with the **Data Engineering** team to **prevent errors** and **improve data quality from the source**. **Key Responsibilities** * Validate **data quality** across the **pipeline** (ingestion, transformation, consumption) * Design and implement **validation rules** and quality controls (**completeness, consistency, accuracy**) * Analyze failures in **datasets** and perform **root cause analysis (RCA)** * Ensure data meets defined **SLAs** (timeliness and quality) * Collaborate closely with Data Engineers to enhance validation processes and prevent errors * Validate **outputs** across data layers (**Bronze, Silver, Gold**) * Participate in validation of **data tickets** (**data refresh, changes, corrections**) * Document quality rules, validations, and findings * Propose process improvements for **data quality** (e.g., cross-layer validation loops) **Technical Requirements** * Minimum **3 years** of experience in **data validation within data engineering environments** * Proficiency in **SQL** for data analysis and validation * Experience with platforms such as **Databricks, Spark, or similar** * Experience working with **data pipelines (ETL / ELT)** * Knowledge of orchestration tools such as **Airflow (preferred)** * Experience with version control (**GitHub**) * Knowledge of data testing (**unit tests, data validation frameworks**) * Familiarity with **data architecture concepts** (**medallion architecture: Bronze, Silver, Gold**) * **Advanced English (spoken and written).** **What We Offer** * Competitive salary based on each candidate’s experience * Remote work * Technical and language training programs * Access to an E-Learning platform If this opportunity fits your profile, don’t hesitate to apply—we look forward to welcoming you!