• Develop and maintain robust, scalable data pipelines (ETL), following engineering best practices and data modeling standards; • Build and maintain databases to meet business objectives and regulatory requirements; • Create and maintain continuous data quality monitoring processes, implementing automated validations and alerting systems to identify and notify about inconsistencies, anomalies, or pipeline failures; • Lead migration of legacy data to Databricks, ensuring integrity, performance, and governance; • Collaborate with analysts and partner teams to ensure understanding of business rules and data consistency; • Support the evolution of the data architecture by evaluating and implementing new tools and processes.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Trumid is seeking a Senior Data Engineer to join our Data & Intelligence team and build the next generation of the real-time data platform that powers Trumid’s pricing algorithms and machine learning systems. - Our pricing infrastructure relies on low-latency, event-driven data pipelines that deliver market and operational data to production algorithms with sub-second latency. - These systems directly support Trumid’s Fair Value Model Pricing (FVMP) and other core data products used across the platform. - This role focuses primarily on real-time streaming infrastructure and distributed data systems that support production algorithms. - Occasional contributions to the batch workloads that the team supports for both research and reporting use cases. - This position is U.S.-based, with remote or hybrid options available. Candidates located in the New York City area are preferred. Qualifications - 5+ years building production data infrastructure or backend systems. - Strong programming skills in Python and SQL. - Experience designing or operating streaming or event-driven data pipelines (Kafka, Flink, or similar systems). - Experience working with distributed systems or real-time data processing. - Experience operating production systems in cloud environments. - Strong understanding of system reliability, monitoring, and failure handling. - Ability to collaborate with engineers, quantitative researchers, and data scientists to deliver reliable data infrastructure. - Enjoy building high-performance distributed systems and operating production infrastructure where latency, reliability, and operational stability are critical. Requirements - Lead the architecture and development of streaming data pipelines that deliver market and operational data to pricing algorithms with sub-second latency, relying on technologies such as Kafka and Flink. - Define architectural standards for real-time data delivery, reliability, and observability. - Ensure production SLAs are met for systems that directly impact pricing and trading workflows. - Collaborate with quantitative researchers, data scientists, and engineers to deliver reliable data inputs for modeling and backtesting. - Mentor engineers on best practices for distributed data systems and production-grade data pipelines. - Contribute to the broader data platform, including batch pipelines and data modeling workflows when needed. Benefits - Highly competitive compensation. - Fully paid medical, dental and vision coverage. - Team-oriented and collaborative company culture. - Flexibility for in-office and work from home arrangements. - In compliance with New York City Pay Transparency Law, the base salary range for this role in New York City is between $200,000 - $250,000. - This range does not include discretionary bonus or other forms of compensation or benefits offered in connection with this job. - Several factors are considered when determining a candidate’s compensation. - Please note that the salary range listed for this position is based on the level of experience outlined in the job description. - If a candidate's experience differs from the requirements, the salary may be adjusted accordingly.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Trumid is seeking a Data Engineer to join our Data & Intelligence team and build the next generation of the real-time data platform that powers Trumid’s pricing algorithms and machine learning systems. - Our pricing infrastructure relies on low-latency, event-driven data pipelines that deliver market and operational data to production algorithms with sub-second latency. - These systems directly support Trumid’s Fair Value Model Pricing (FVMP) and other core data products used across the platform. - This role focuses primarily on real-time streaming infrastructure and distributed data systems that support production algorithms. - It will also include occasional contributions to the batch workloads that the team supports for both research and reporting use cases. - This position is U.S.-based, with remote or hybrid options available. Candidates located in the New York City area are preferred. Qualifications - 2–5 years building production data systems or backend infrastructure. - Strong programming skills in Python and SQL. - Experience building or operating streaming or event-driven data pipelines (Kafka, Flink, or similar systems). - Familiarity with distributed systems or real-time data processing architectures. - Experience operating production systems in cloud environments. - Strong problem-solving skills and interest in building reliable data infrastructure. - You enjoy building high-performance data systems, working closely with experienced engineers, and contributing to infrastructure that powers real-time decision-making. Requirements - Lead the architecture and development of streaming data pipelines that deliver market and operational data to pricing algorithms with sub-second latency, relying on technologies such as Kafka and Flink. - Ensure production SLAs are met for systems that directly impact pricing and trading workflows. - Collaborate with quantitative researchers, data scientists, and engineers to deliver reliable data inputs for modeling and backtesting. - Contribute to the broader data platform, including batch pipelines and data modeling workflows when needed. Benefits - Highly competitive compensation. - Fully paid medical, dental and vision coverage. - Team-oriented and collaborative company culture. - Flexibility for in-office and work from home arrangements. - In compliance with New York City Pay Transparency Law, the base salary range for this role in New York City is between $175,000 - $225,000. - This range does not include discretionary bonus or other forms of compensation or benefits offered in connection with this job. - Several factors are considered when determining a candidate’s compensation.

• Design, develop, and maintain robust, scalable ETL/ELT pipelines for ingesting, transforming, and storing data from multiple sources into centralized repositories. • Lead the design, development, and deployment of interactive Power BI dashboards and reports. • Ensure consistency, usability, and performance of BI solutions across the organization. • Create and optimize data models to support self-service analytics and enterprise reporting. • Partner with stakeholders across departments to gather requirements, translate business needs into technical solutions. • Optimize database queries, DAX calculations, Power BI datasets, and storage models for efficiency and scalability. • Implement data governance practices, establish validation rules, and maintain high standards for data integrity and accuracy. • Maintain thorough documentation of data architecture, data flows, and reporting standards. • Promote best practices in BI development and data engineering