Data Engineer

This is a fully remote position, open to applicants in New York.

📋 Description

• Create, develop, and sustain production-quality data pipelines and data-centric systems.

• Set up, schedule, and oversee data pipeline execution to guarantee reliability, maintainability, and punctual delivery across all data operations.

• Deploy and manage data infrastructure on AWS or on-premises while ensuring scalability, security, and cost-effectiveness.

• Monitor and enhance the performance of relational and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB) to ensure efficient querying, indexing, and data accessibility at scale.

• Ensure the reliable ingestion, transformation, and availability of extensive and time-series financial data, taking into account the unique data quality characteristics of financial information.

• Implement and uphold data quality, validation, and monitoring mechanisms throughout data workflows.

• Define and refine data models and storage structures across relational and NoSQL systems.

• Collaborate with Data Scientists and Analysts to facilitate accurate and efficient data access for analytics and modeling purposes.

• Enhance data processing workflows for optimal performance, reliability, and operational stability.

• Diagnose complex data issues and conduct root cause analysis.

• Contribute to technical decision-making and assist in outlining the roadmap for data infrastructure.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, or a related discipline.

• Proficient programming skills in Java or Python (or other JVM-based languages).

• In-depth understanding of data modeling, SQL, and NoSQL databases.

• Strong emphasis on data quality, validation, and monitoring practices.

• Experience with large-scale and time-series datasets in financial settings, along with an understanding of their structure and prevalent data quality issues.

• Proven experience in building and maintaining production data pipelines or data-intensive systems, with an emphasis on reliability and performance.

• Capability to troubleshoot and optimize production data systems.

• Familiarity with workflow orchestration and data pipeline scheduling tools.

• Solid grasp of financial data structures and concepts, with the ability to model and validate financial data accurately.

• Excellent problem-solving capabilities and attention to detail.

• Professional proficiency in English.

🏝️ Benefits

• Competitive salary and a genuinely flexible work environment.

• Access to an unlimited learning and development budget to stay at the forefront of AI research.

• Annual company retreat at a breathtaking location.

• Accelerated career progression with opportunities to advance into leadership roles.