Data Platform Tester
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Summary
Törökbálint, HUN
Hybrid
Medior
Introduction
Telekommunikációs partnerünk egy modern, AWS alapú adatplatform fejlesztésén dolgozó csapatába keres új kollégát Data QA / ETL Testing Engineer pozícióba. A szerepkör fókuszában az adatminőség biztosítása, ETL/ELT folyamatok validációja, valamint automatizált testing és monitoring megoldások kialakítása áll.
Description
Tasks & Responsibilities
- Data Validation & Quality Checks
- Verify data accuracy, completeness, and consistency across sources.
- Check for duplicates, missing values, and schema mismatches.
- Validate transformations and aggregations against business logic.
- Create tools to detect and validate source schema changes.
- ETL/ELT Testing
- Test data pipelines for correct extraction, transformation, and loading.
- Ensure jobs run within expected timeframes, handle edge cases.
- Maintain the required logging and alerting workflows.
- Integration Testing
- Validate integration between different components (e.g., ingestion tools, data lake ETL processes, source DBs, APIs).
- Test compatibility with upstream and downstream systems.
- Performance & Scalability Testing
- Assess query performance and pipeline throughput.
- Simulate large data volumes to ensure the platform scales properly.
- IaC & Automation
- Develop automated DQ rules and test scripts for recurring checks (e.g., schema validation, data profiling).
- Use frameworks like pytest, Python Deequ or AWS Glue Data Quality for data quality.
- Create the required IaC test modules and ensure they are integrated and deployed with CI/CD pipelines
- Security & Compliance Testing
- Validate data access controls, encryption, and compliance with GDPR or other regulations.
- Regression Testing
- Ensure new changes do not break existing functionality.
- Reporting & Documentation
- Document test cases, results, and defects.
- Communicate findings to developers, data engineers, and stakeholders.
Tasks
- Adatvalidációs és data quality ellenőrzések kialakítása és futtatása
- ETL/ELT pipeline-ok tesztelése és hibakeresése
- Adattranszformációk és aggregációk ellenőrzése üzleti logika alapján
- Schema változások detektálása és validációja
- Integration és regression testing különböző adatplatform komponensek között
- Pipeline-ok teljesítményének és skálázhatóságának tesztelése
- Automatizált data quality szabályok és tesztek fejlesztése
- CI/CD pipeline-okba integrált testing folyamatok kialakítása
- Logging, monitoring és alerting folyamatok támogatása
- Tesztesetek, hibák és eredmények dokumentálása
- Szoros együttműködés data engineer, developer és stakeholder csapatokkal
Expectations
- Magabiztos SQL tudás
- Tapasztalat Python és/vagy PySpark használatában
- ETL/ELT folyamatok ismerete
- Gyakorlat automatizált tesztelési megoldások kialakításában
- AWS környezetben szerzett tapasztalat
- pytest vagy hasonló testing framework ismerete
- Git és CI/CD pipeline-ok magabiztos használata
- Jó problémamegoldó és analitikus gondolkodásand compliance standards is a plus.
Advantages
- Airflow vagy dbt tapasztalat
- Deequ, Great Expectations vagy AWS Glue Data Quality ismerete
- Data governance és compliance területen szerzett tapasztalat
- Infrastructure as Code (IaC) szemlélet
Employer's offer
- Modern, cloud alapú technológiai környezet
- Stabil, hosszú távú projektlehetőség
- Szakmai fejlődési lehetőség data engineering és data quality területen
- Nemzetközi projektek és modern adatplatform technológiák
- Támogató, együttműködő csapat
- Versenyképes juttatási csomag
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