Data Engineer

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🕒 vor 1 Monat

🗽 New York – Remote

🗽 New York – Remote

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

🚰 Dateningenieur

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MdotM

WebsiteLinkedInAlle Stellen

11 - 50 Mitarbeiter

Gegründet 2009

MdotM ist eine leistungsbasierte mobile Demand-Side-Plattform, die mehr als 300 Millionen einzigartige Nutzer auf iOS und Android erreicht. Die MdotM Demand-Side-Plattform ermöglicht es Werbetreibenden und Agenturen, ihre Zielgruppe effizient in Echtzeit zu erreichen, indem sie Zugang zu Milliarden von monatlichen mobilen Anfragen erhalten.

Beschreibung

• Design, build, and maintain production-grade data pipelines and data-intensive systems • Configure, schedule, and monitor data pipeline execution to ensure reliability, maintainability, and timely delivery across all data processes • Deploy and manage data infrastructure on AWS or on-premises, ensuring scalability, security, and cost-efficiency • Monitor and optimize relational and NoSQL database performance (e.g., MySQL, PostgreSQL, MongoDB) to ensure efficient querying, indexing, and data access at scale • Ensure reliable ingestion, transformation, and availability of large-scale and time-series financial data, considering financial-specific data quality characteristics • Implement and maintain data quality, validation, and monitoring mechanisms across data workflows • Define and evolve data models and storage structures across relational and NoSQL systems • Collaborate with Data Scientists and Analysts to ensure accurate and efficient data access for analytics and modeling use cases • Optimize data processing workflows for performance, reliability, and operational stability • Troubleshoot complex data issues and drive root cause analysis • Contribute to technical decision-making and help define the roadmap for data infrastructure.

🎯 Anforderungen

• Degree in Computer Science, Engineering, or a related field • Strong programming skills in Java or Python (or other JVM-based languages) • Strong understanding of data modeling, SQL, and NoSQL databases • Strong focus on data quality, validation, and monitoring practices • Experience working with large-scale and time-series datasets in financial contexts, with an understanding of their structure and common data quality challenges • Experience building and maintaining production data pipelines or data-intensive systems, with focus on reliability and performance • Ability to troubleshoot and optimize production data systems • Experience with workflow orchestration and data pipeline scheduling tools • Solid understanding of financial data structures and concepts, with the ability to model and validate financial data accurately • Strong problem-solving skills and attention to detail. • Professional proficiency in English.

🏖️ Vorteile

• Competitive salary & truly flexible work environment • Benefit from an unlimited learning and development budget to stay at the bleeding edge of AI research • Annual company retreat at a stunning location • Fast-track career progression, with opportunities to grow into leadership roles