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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Lead Software Engineer, Big Data & Cloud Engineering - Risk Central (London) - **Company:** JPMorgan Chase & Co. - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Java (Programming Language), Amazon Web Services, Amazon S3, Data Analysis, Big Data, Cloud Computing, Cloud Engineering, Code Review, Continuous Integration, Data Governance, Data Structures, Data Warehousing, DevOps, Distributed Computing Environment, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Networking Basics, Object-Oriented Software Development, Performance Tuning, SQL Databases, Data Streaming, Enterprise Data Management, Parquet, Apache Spark, Build Management, Containerization, Infrastructure Automation Frameworks, Apache Kafka, Video Streaming, Data Pipelines, Amazon Redshift, Databricks - **Published:** September 24, 2026 - **Apply:** https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/requisitions/preview/210784401 ## About the Role * Demonstrated experience delivering production software systems at scale. * Proficiency in Python and or Java or Scala, with computer science fundamentals including data structures, algorithms, and object-oriented design. * Hands-on experience with distributed data processing, such as Spark, and building data pipelines in batch and or streaming patterns. * Experience with Databricks, Amazon Redshift, or equivalent enterprise data warehouse and lakehouse platforms, including designing and tuning performant workloads. * Proficiency in SQL and understanding of data modeling and analytics patterns. * Practical knowledge of cloud engineering concepts, including security, networking basics, IAM and access controls, encryption, and observability. * Proven ability to troubleshoot production issues and drive operational improvements. * Strong communication skills and experience working with globally distributed teams., * Experience in Markets technology, including familiarity with the trade lifecycle, market risk measures, sensitivities, and P&L explain, plus common products such as FX, rates, credit, and equities. * Experience with streaming technologies and near-real-time analytics patterns, including Kafka, MSK, or Kinesis. * Experience with governance, controls, and data quality frameworks including reconciliations, lineage, auditability, and entitlements. * Familiarity with lake and lakehouse table formats and concepts, including Iceberg or Delta, and columnar storage formats such as Parquet. * Experience with CI/CD, infrastructure as code, containerized workloads, and DevOps practices. * Experience leading initiatives across multiple teams, including technical leadership, mentoring, and cross-team coordination. ## Description Build and operate data and analytics services that power critical markets risk decisions at scale. In this senior, hands-on role, you will lead complex engineering initiatives across a modern cloud and big data stack while shaping technical direction and standards. You will partner closely with stakeholders across Front Office, Risk, Product Control, and Finance to deliver timely, consistent, high-quality analytics. You will help strengthen reliability, governance, and performance across enterprise data platforms, including Databricks and Amazon Redshift., As a Senior Lead Software Engineer at JPMorgan Chase in the Risk Central team, you will be a senior hands-on engineer and technical leader responsible for building and operating scalable data and analytics services supporting Markets risk use cases. You will lead delivery across ingestion, transformation, storage, and consumption layers, with a strong focus on operational excellence and predictable outcomes. You will design and evolve data products and workflows that run across Databricks and Amazon Redshift, improving consistency, controls, and performance. You will mentor engineers, drive engineering best practices, and communicate clearly on progress, risks, dependencies, and trade-offs., * Lead end-to-end delivery of complex initiatives across ingestion, transformation, storage, and consumption layers. * Drive engineering best practices including design reviews, code reviews, testing standards, CI/CD, and documentation. * Mentor engineers and raise the bar on technical quality, ownership, and operational excellence. * Design and build robust batch and streaming pipelines using distributed compute for high-volume workloads. * Implement efficient data modeling, partitioning, and performance tuning strategies for large datasets. * Build reusable frameworks and components to accelerate onboarding of new datasets and analytics use cases. * Engineer data products and workflows spanning Databricks and Amazon Redshift, including ingestion patterns, transformations, and serving layers. * Define approaches to reconciliation, consistency, lineage, and controls across both enterprise data warehouses. * Optimize query performance and cost across platforms, and establish best practices for workload placement. * Build cloud-native solutions on AWS aligned to team standards, including services such as S3, EMR, Lambda, Kinesis or MSK, Glue, EventBridge, DynamoDB, Redshift, and EKS. * Own production stability by improving monitoring and alerting, incident management, root-cause analysis, preventative engineering, and SLAs and SLOs. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Enterprise-Cloud-Native - Fast-Paced Development & Deployment in a Highly Secure Banking Environment](https://www.wearedevelopers.com/videos/671-enterprise-cloud-native-fast-paced-development-deployment-in-a-highly-secure-banking-environment) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [OLAP for AI Applications and why you should care](https://www.wearedevelopers.com/videos/100212-olap-for-ai-applications-and-why-you-should-care) ## Related Articles - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Best Companies to work for in London: Top 25 Companies in 2023](https://www.wearedevelopers.com/magazine/187-best-companies-to-work-for-in-london-top-25-companies-in-2023) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers)