Design Build and Maintain Cloud-Native Software Services and Data Pipelines
Design build and maintain cloud-native software services and data pipelines that support Big Data and Enterprise Analytics solutions. Partner with product and technical leads to translate requirements into well-scoped designs, implementation plans, and deliverables. Implement new features and enhancements in existing applications and services with a focus on reliability, maintainability, and operational excellence. Troubleshoot, debug, and resolve issues across the stack, performing root-cause analysis and driving fixes to completion. Improve system performance through profiling, optimization, and effective use of concurrency and data-access patterns. Produce clear technical documentation and artifacts, design notes, flow diagrams, and runbooks to support development and ongoing operations. Collaborate with engineering teams through code reviews, testing, and continuous improvement to deliver high-quality software.
Requirements
Bachelors degree in Computer Engineering or related field with 5 years of experience or Masters degree with 3 years experience or a PhD with no previous professional experience or equivalent experience. Experience with Python and Java. Excellent knowledge of object-oriented software design and implementation. Experience developing cloud-native applications and data pipelines on Azure, including event-driven, batch, and serverless architectures (e.g., Event Grid, Event Hub, Azure Functions, Azure Batch). Experience building and optimizing big data pipelines, including ingestion, transformation, and persistence using Azure Data Lake Storage (ADLS) and related analytics services. Experience developing enterprise analytics software on cloud infrastructure, including data processing, indexing, and query enablement (e.g., HDInsight, Azure AI Search, Azure SQL, Cosmos DB). Experience implementing distributed data processing systems leveraging caching, orchestration, and background execution (e.g., FastAPI, Celery, Redis) to improve performance and scalability.
Analytical and Technical Skills
Strong analytical problem-solving and troubleshooting skills. Excellent verbal and written communication skills. Ability to work and thrive in a fast-paced environment, learn rapidly, and master diverse technologies and techniques. Familiarity with lakehouse table formats (e.g., Iceberg) and columnar storage formats (e.g., Parquet). Working knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes). Experience with stream processing technologies (e.g., Apache Kafka, Spark Streaming) in enterprise analytics environments. Familiarity with Continuous Integration and Continuous Deployment (CICD) and software development lifecycle tooling (e.g., Azure DevOps, Git, Jira, Confluence, Maven, Jenkins). Experience working in Agile Scrum teams, contributing to sprint planning, execution, and continuous improvement. Solid understanding of computer system architecture fundamentals, processes, memory, storage, networking, and their impact on large-scale data processing. Experience in the semiconductor equipment manufacturing industry is a plus.
From smartphones and tablets to wearables and automobiles, it’s hard to go more than a few hours without using a semiconductor-enabled device. The semiconductor industry touches nearly every person on the planet, and chipmakers continue to advance the technology that powers it all.
As a trusted partner to the world’s leading semiconductor companies, we welcome challenges and we deliver. That’s why, today, nearly every advanced chip is built with Lam technology.
Our innovative wafer fabrication equipment and services allow chipmakers to build smaller and better performing devices. We combine superior systems engineering, technology leadership, and a strong values-based culture, with an unwavering commitment to our customers.