Job specification: trading data platform developer – trading technology

Location: India (Offshore Development Centre) US Based MNC - Roles - as soon they establish  in Function: Trading Technology / Data Platform Engineering Reports To: Trading Data Engineering Development Lead – London Role Type: Full-Time, Permanent Work Schedule: Aligned with UK and US trading hours (rotational or extended coverage) Overview Our client, a leading global commodity trading house, is expanding its Trading Data Engineering team in India to support the delivery of high-quality market and fundamental data platforms that power trading, analytics, and risk functions across global desks. The Trading Data Platform Developer will focus on engineering scalable data services and access layers, including APIs and Excel-based integrations, in a cloud-native (AWS-hosted) environment. The role requires deep technical proficiency in Python-based microservices (e.g., Fast API ), data engineering pipelines, and containerized deployments using Kubernetes and Docker . This is a hands-on engineering position, working closely with global teams in London, Houston, and Singapore to ensure the reliability, performance, and scalability of data systems supporting Oil, Gas, and Power trading. Key Responsibilities 1. Data Platform Engineering Design, build, and maintain data pipelines ingesting market data, fundamental data , and reference datasets from internal and external sources. Develop and optimize ingestion frameworks, transformations, and access layers using Python , AWS services (Glue, Lambda, ECS, S3, Athena, Redshift) , and streaming tools such as Kafka . Collaborate with data scientists, analysts, and quants to ensure data accessibility for trading, pricing, and risk analytics. 2. API and Data Access Layer Development Develop and maintain RESTful APIs using Fast API to serve market and fundamental data to internal applications and dashboards. Build scalable and performant Excel Add-ins and other client interfaces for traders and analysts to access real-time and historical data. Manage authentication, authorization, and throttling for data access services, ensuring security and compliance. 3. Cloud-Native Infrastructure and Dev Ops Deploy and manage applications using Docker containers and Kubernetes pods in AWS-hosted environments. Implement CI/CD pipelines (Git Hub Actions, Jenkins) for automated testing, deployment, and release management. Monitor application health and performance using Cloud Watch , Grafana , or Prometheus , ensuring resilience and observability. 4. Collaboration and Continuous Improvement Partner with global Data Engineering, Market Data, and Risk Technology teams to align platform enhancements with business priorities. Contribute to data quality monitoring, lineage tracking, and metadata management initiatives. Drive continuous improvement by automating repetitive processes and adopting new frameworks or tools that enhance performance and maintainability. Key Skills and Experience Technical Skills Strong proficiency in Python and experience with frameworks such as Fast API or Flask for microservice development. Hands-on experience with AWS cloud ecosystem , including Lambda, ECS, EKS, S3, Glue, Cloud Formation, and IAM. Solid understanding of containerization (Docker) and orchestration using Kubernetes . Experience with data pipelines , streaming frameworks (Kafka, Kinesis), and distributed data processing. Familiarity with SQL and data warehouse technologies (Redshift, Snowflake, or similar). Exposure to API authentication and security (OAuth2, JWT) and Excel integration (COM Add-ins, xlwings, or similar). Experience with CI/CD , testing automation , and Git-based workflows . Soft Skills Strong communication and collaboration skills across global time zones and functional teams. Analytical thinker with a structured approach to problem-solving in high-pressure trading environments. Demonstrates initiative in identifying and delivering automation or efficiency improvements. Detail-oriented with a commitment to clean, maintainable, and well-documented code. Experience 5–10 years of total experience in data engineering, platform development, or trading technology. Prior experience in commodity trading, investment banking, or financial data engineering preferred. Proven experience developing and deploying cloud-native applications in AWS. Exposure to global support and development collaboration models advantageous. Education Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline. Success Indicators Delivery of reliable and high-performance data APIs and access layers supporting trading and analytics. Demonstrated ability to deploy and scale containerized workloads in production. Reduction in latency and improvement in data availability metrics across critical systems. Positive feedback from trading and data stakeholders regarding platform stability and usability. Why This Role Matters This role is foundational to building a scalable and resilient trading data platform that enables real-time decision-making across global commodity markets. As the offshore center grows, the position offers strong career progression towards Senior Data Engineer or Technical Lead roles within the global Trading Technology organization