Entry Level

This job independently executes key elements of projects/processes within the Software Engineering area by applying in-depth knowledge of their discipline and area best practices to effectively resolve problems and roadblocks as they occur. Contributes to the development and maintenance of high-quality, scalable software solutions, supporting security and operational resilience with guidance. Participates in code reviews, providing feedback to help uphold quality standards and best practices. Assists in designing, developing, and delivering software solutions that align with business needs and organizational standards, with oversight. Creates and maintains technical artifacts, such as requirements documents, design specifications, and test plans, supporting project documentation efforts. Supports system maintenance activities, including incident management, root cause analysis, and problem resolution in production environments, with supervision. Contributes to solution and technology roadmaps, providing input to support strategic planning and innovation initiatives. May contribute to solution development for new products/services and/or manage smaller project/initiatives as an experienced individual contributor with specialized knowledge within the Software Engineering area. You will build innovative products that help businesses around the world unlock more value from their data. As a Senior Software Development Engineer within EDE, you will contribute to full-stack, data-intensive, analytics-driven applications that support sophisticated business experimentation and decision-making for some of the world’s largest organizations. Design, build, and maintain scalabledata platforms, distributed systems, and enterprise integration solutions across both on-premises and cloud environments. Develop and optimize data-intensive applications leveraging Databricks, Spark, and related platforms to efficiently process, transform, and serve data. Build features that support enterprise data onboarding, exchange, discovery, and consumption capabilities. Contribute to architecture and system design, collaborating with cross-functional teams to deliver scalable, high-quality solutions aligned with engineering best practices. Write clean, maintainable, and efficient code, applying strong practices in testing, code reviews, and continuous improvement. Identify and resolve performance bottlenecks across services, APIs, data-processing workloads, and user experience. Collaborate with Product, Engineering, Data Governance, Security, and business stakeholders to understand requirements for your area of work. Continuously learn and improve, staying current with technologies and driving enhancements in quality, scalability, and developer productivity. The ideal candidate is a collaborative, technically strong full-stack engineer who is passionate about building scalable, data-intensive platforms. They are comfortable working across application, service, and data-processing layers and can contribute effectively in a fast-paced, agile engineering environment. Experience as a full-stack Software Engineer, with exposure to building platforms using modern technologies such as Java/Spring Boot, TypeScript, and React. Experience building large-scale data platforms, distributed systems, and enterprise integration solutions across both on-premises and cloud environments, leveraging technologies such as Spark, Kafka, Flink, NiFi, Hadoop/Cloudera, Databricks, and modern cloud-native data services. Experience integrating AI driven capabilities into data platforms, with appropriate governance and guardrails for emerging use cases, including agentic commerce. Experience building reusable platforms that serve multiple products, teams, or business domains. Foundational understanding of software engineering principles, including object-oriented programming, API design, and scalable system design, is preferred. Interest in working with data-intensive applications, including improving performance, scalability, and reliability across services and data-processing layers. Curiosity, self-motivation, and a strong willingness to learn, with a growth mindset and interest in solving analytical, data-driven problems in an agile, fast-paced environment. Bachelor’s or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience #