Data Engineer

Emploi pas sur LinkedIn

🕒 il y a 1 mois

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🚰 Ingénieur Data

🦅 Parrain de Visa H1B

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Ardent

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2008

💼 Conseil

🎖️ Défense

📦 Logistique

Consulting • Defense • Logistics

Ardent est une entreprise technologique de premier plan au service du secteur public, dédiée à la fourniture de solutions cruciales pour les missions. Ils se spécialisent dans la science des données et l'analytique, la transformation numérique et l'intelligence géospatiale, aidant les organisations à prendre de meilleures décisions, à moderniser leurs systèmes et à déchiffrer les données spatiales. Ardent s'engage à se défendre contre les menaces d'origine humaine et naturelle, en offrant des solutions efficaces telles que les applications cloud, la cybersécurité et la science des données spatiales. Ils collaborent étroitement avec des agences fédérales, y compris le Département de la Sécurité Intérieure, pour assurer la sécurité nationale. Leurs solutions sont conçues pour prospérer dans des environnements complexes, éprouvées dans des études de cas et livrées avec la rapidité et la précision requises par les missions de leurs clients.

Description

• Design, develop, and maintain scalable ETL/ELT pipelines to support enterprise data integration and analytics. • Ingest, transform, and integrate data from diverse sources, including flat files, JSON, XML, Excel, REST APIs, graph databases, and other structured and unstructured data formats. • Develop and optimize SQL and Python-based data processing solutions to support efficient data ingestion and transformation. • Build and maintain reusable, scalable data workflows that support business intelligence, reporting, and advanced analytics. • Load, manage, and optimize data within modern data platforms, including Databricks Unity Catalog and SQL Server Managed Instances. • Support both batch and streaming data ingestion frameworks. • Implement and maintain modern Lakehouse architecture solutions to improve scalability, performance, and accessibility. • Monitor and optimize database and pipeline performance to ensure efficient processing and storage. • Implement data quality controls to ensure the accuracy, consistency, reliability, and integrity of enterprise data. • Maintain data lineage and metadata to support governance and regulatory compliance. • Apply enterprise data management (EDM) standards and best practices throughout the data lifecycle. • Support data governance initiatives, including documentation, validation, and quality assurance activities. • Collaborate with cross-functional teams, including data analysts, software developers, architects, and business stakeholders, to understand data requirements and deliver effective solutions. • Support analytical environments focused on fraud detection, anomaly detection, financial oversight, and other data-driven initiatives. • Troubleshoot and resolve data pipeline, integration, and performance issues while continuously improving existing processes.

🎯 Exigences

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field (or equivalent combination of education and experience). • Minimum of 3 years of professional experience in data engineering or a related field. • Demonstrated experience designing, building, and maintaining scalable ETL/ELT pipelines across multiple data sources. • Strong proficiency in SQL and Python or equivalent technologies used for data engineering and transformation. • Experience ingesting and transforming data from a variety of formats, including: • Flat files • JSON • XML • Microsoft Excel • REST APIs • Graph databases • Additional structured and unstructured data sources • Experience working with Databricks Unity Catalog, SQL Server Managed Instances, or comparable enterprise data platforms. • Experience with streaming and batch ingestion frameworks and modern Lakehouse architecture. • Strong understanding of data quality, data lineage, performance optimization, and enterprise data management principles. • Familiarity with data governance, data quality, and data management practices aligned with Enterprise Data Management (EDM) standards. • Experience supporting fraud detection, anomaly detection, financial oversight analytics, or similar analytical environments is preferred. • Excellent analytical, problem-solving, and communication skills with the ability to collaborate effectively across technical and business teams. • Must be willing to undergo a U.S. Government background investigation.

🏖️ Avantages

• competitive pay • comprehensive health coverage • flexible PTO • federal holidays off • tuition reimbursement • professional development support • wellness stipends • culture that values and rewards hard work, dedication, and adaptability