Data Engineer

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Cybermedia Technologies, LLC (CTEC)

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201 - 500 employés

Fondée en 1996

💼 Conseil

🏥 Santé

📦 Logistique

Consulting • Healthcare • Logistics

Cybermedia Technologies, LLC (CTEC) est une entreprise dédiée à la modernisation des infrastructures informatiques obsolètes et à la sécurisation des systèmes essentiels pour les agences fédérales. Avec plus de 25 ans d'expérience, CTEC se spécialise dans la modernisation informatique, les services de cybersécurité et de cloud, ainsi que dans les solutions de formation de la main-d'œuvre qui favorisent l'adoption technologique et l'efficacité au sein des opérations gouvernementales. Leur approche innovante se concentre sur la mise en œuvre d'une conception centrée sur l'humain pour impacter quotidiennement des millions de travailleurs fédéraux et de citoyens américains.

Description

• Design, develop, and maintain scalable ETL pipelines and data workflows. • Build, optimize, and maintain data processing solutions using Azure Databricks. • Support phased data migration from legacy databases and ETL tools. • Implement layered lakehouse data architectures in Databricks. • Develop data processing notebooks, workflows, and distributed data transformations using Python and PySpark. • Develop data validation, reconciliation, and testing processes. • Integrate Databricks data platforms with analytics and reporting tools. • Support data governance initiatives including metadata management. • Maintain source control and CI/CD pipelines for Databricks workflows. • Provide ongoing support for Databricks workflows and troubleshoot complex issues. • Provide guidance to junior data engineers and contribute to documentation and team enablement.

🎯 Exigences

• At least seven (7–9+) years of experience in data engineering, ETL development, or large-scale data integration environments. • Strong experience designing and developing ETL pipelines and data transformations in Azure Databricks environments. • Strong proficiency in SQL and Python, with hands-on experience using PySpark for distributed data processing. • Experience working with cloud-based data platforms, data lakes, and lakehouse environments, preferably on Microsoft Azure. • Experience implementing layered lakehouse data architectures (bronze, silver, gold) for enterprise analytics. • Familiarity with Spark-based big data processing frameworks. • Experience supporting data migration from legacy databases and ETL tools to Databricks-based platforms. • Experience integrating Databricks platforms with business intelligence and reporting tools such as Power BI. • Familiarity with data governance, metadata management, and data security best practices. • Experience with source control and CI/CD pipelines for data engineering and Databricks workflows. • Working knowledge of SDLC and Agile delivery methodologies. • Excellent organizational, communication, and collaboration skills.

🏖️ Avantages

• Paid vacation & Sick leave • Health insurance coverage • Career training • Performance bonus programs • 401K contribution & Employer Match • 11 Federal Holidays