> Markdown version of [/jobs/ext/3043809-software-engineer-ii](https://www.wearedevelopers.com/jobs/ext/3043809-software-engineer-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer II - **Company:** New Relic, Inc. - **Location:** Spain - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Automation of Tests, BigQuery, Software Bug Management, Cloud Computing, Extract Transform Load (ETL), Data Visualization, Dimensional Modeling, Distributed Computing Environment, Distributed Systems, Apache Hadoop, Apache Hive, Queueing Systems, Recommender Systems, Tableau (Software), Workflow Management Systems, Large Language Models, Snowflake, Concurrency, Apache Spark, Kubernetes, Apache Kafka, Free and Open-Source Software, Graphql, Asynchronous Programming, Looker Analytics, Sql Tuning, Amazon Redshift, Microservices - **Published:** September 24, 2026 - **Apply:** https://startup.jobs/software-engineer-ii-new-relic-company-10166095 ## About the Role * Fully proficient with Java, with the ability to design, develop, test, and deploy small-to-medium features and bug fixes end-to-end with little or no assistance * Experience building Kafka-based streaming pipelines and services in a cloud (AWS) production environment * Experience with distributed systems, concurrency, and scaling, and familiarity with asynchronous programming techniques (streams, event-based flows, task queues, message queues) * Active experience using AI coding assistants and agents in your day-to-day engineering workflow, with a mindset of continuous workflow innovation * A collaborative work style that includes colleagues in important decisions and leads to shared code ownership * Comfortable navigating ambiguity with an iterative mindset, and able to align day-to-day work with broader strategic and architectural direction * Proficiency in English Bonus points if you have * Experience designing GraphQL APIs or microservices architectures at scale * Familiarity with Kubernetes concepts and ability to reason about production behavior * Experience with distributed data processing in the cloud (Spark, Hadoop/Hive, BigQuery, Snowflake, Redshift) or ETL/orchestration tools such as Airflow * Strong understanding of data modeling principles (dimensional modeling, normalization), especially applied to behavioral or user segmentation * Proven experience evaluating, benchmarking, or building custom agentic AI tools, prompt workflows, or developer automation * Exposure to recommendation systems or building context for agentic/LLM-based experiences * Contributions to open source projects, or a passion for build/test automation * Experience with SQL performance tuning or data visualization tools (Tableau, Looker) ## Description * Build, maintain, and scale backend services and Kafka-based streaming pipelines that process user behavior data across our AWS infrastructure * Design microservices and APIs that expose user segments and behavioral models to downstream surfaces, both classic UI and agentic * Turn behavioral signals into segments and models the rest of the platform builds on * Actively use and evaluate AI coding assistants and agents in your own engineering workflow. From code generation and review to production troubleshooting and help the team adopt what works * Participate in architectural discussions, exercising judgment to determine the right approach on moderately scoped problems * Build, deploy, rollback, and operate your team's software, including active participation in on-call * Automate manual operational processes with new tooling to keep systems resilient and easy to operate * Provide constructive, service-level-aware feedback and actively participate in engineering communities of practice ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story) - [GraphQL + Apollo + Next.js: A Lovely Trio](https://www.wearedevelopers.com/videos/311-graphql-apollo-next-js-a-lovely-trio) ## Related Articles - [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) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london)