Data Engineer

Job not on LinkedIn

🕒 June 11

🗽 New York – Remote

🗽 New York – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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MdotM

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2009

MdotM is a performance-based mobile Demand Side Platform reaching more than 300MM unique users across iOS and Android. The MdotM Demand Side Platform allows advertisers and agencies to efficiently reach their target audience in real-time by gaining access to billions of monthly mobile ad requests

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• 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