Senior Data Engineer – Data Quality, Observability

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Softgic

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2011

💼 Conseil

🤝 B2B

🤖 Intelligence artificielle

Consulting • B2B • Artificial Intelligence

Softgic est une entreprise de services de transformation numérique et cognitive qui propose des solutions personnalisées pour le développement de logiciels, l'automatisation, le cloud et la cybersécurité, ainsi que des technologies émergentes aux entreprises clientes. Avec plus de dix ans d'expérience, Softgic offre des "labs" spécialisés pour la Conception de Solutions (UX, Agile, design de processus), le Développement (codage, low-code, mobile, DevOps), le Métavers (VR/AR, blockchain, NFTs, économie virtuelle), les Données (Big Data, BI, IA/ML), l'Automatisation (RPA, BPM) et la Mise en Production (cloud, opérations IT, cybersécurité). La société met l'accent sur des services personnalisés axés sur l'entreprise, avec des équipes dédiées et des engagements basés sur les projets pour aider les clients à moderniser l'infrastructure, rationaliser les processus et adopter des technologies avancées.

Description

• Design and implement a scalable data quality framework across the platform. • Lead the implementation and operationalization of GX Core (Great Expectations) as the primary data validation framework. • Develop and maintain reusable data quality rules using a Rule-as-Code approach. • Create automated validation checks for business-critical datasets and workflows. • Implement data observability, monitoring, alerting, and reporting solutions. • Define and maintain data lineage across key business domains. • Design validation processes for data completeness, accuracy, integrity, consistency, reconciliation, freshness, and anomaly detection. • Integrate data quality validations into CI/CD pipelines and release processes. • Develop dashboards and reports to monitor data quality trends and operational health. • Investigate root causes of recurring data issues and implement preventive solutions. • Collaborate with Data Engineering, Application Engineering, QA, Product, and Support teams to establish ownership and governance for data quality. • Define standards for governance, validation frequency, remediation workflows, and quality metrics. • Continuously improve data quality processes and establish long-term observability best practices.

🎯 Exigences

• 5+ years of experience as a Data Engineer or in similar data engineering roles. • Strong experience designing and implementing enterprise Data Quality frameworks. • Hands-on experience with GX Core (Great Expectations) or similar tools such as Soda. • Strong SQL skills and experience working with Aurora PostgreSQL and Amazon Redshift. • Experience designing data validation rules, reconciliation processes, and observability solutions. • Experience building and maintaining ETL pipelines and large-scale data workflows. • Strong understanding of data modeling, referential integrity, synchronization, and batch processing. • Experience integrating data validation into CI/CD pipelines. • Experience with Git and engineering best practices such as Rule-as-Code. • Experience building dashboards, alerts, and reporting for operational monitoring. • Strong analytical and problem-solving skills with experience performing root cause analysis. • Experience collaborating with cross-functional engineering teams. • Excellent communication and documentation skills.

🏖️ Avantages

• Fully remote position. • Opportunity to build enterprise-scale data quality and observability solutions. • High-impact role with ownership over data quality strategy and engineering best practices. • Collaborative environment working alongside Data Engineering, QA, Product, and Application Engineering teams. • Opportunity to work with modern data validation, observability, and cloud data technologies while driving continuous improvement across the platform.