Performance Engineer
1 week ago
Apple Pay brought mobile payment to millions of customers, and it's just the beginning. We are looking for engineers who enjoy both hands-on technical work and designing thoughtful, scalable services for Wallet and Apple Pay. Our team's vision is to be the engine of intelligent transformation, leveraging a unified, reliable data platform to build and deploy innovative and solutions that drive significant business impact and enable data-driven decision-making throughout the organization. Collaborate cross-functionally with architecture, platform design, and software teams to deliver exceptional end-to-end performance that delights our customers.
Description
In this role, you'll be responsible for the performance of one or more products. Specifically, you'll be tasked with ensuring the end-to-end performance of data consumption products. This position demands technical expertise and depth to work on various elements of the stack, from data storage to the platform to BI stack. You'll collaborate with engineering teams to define the product and set its power and performance targets and with the operations team to assess end-to-end performance and develop automation and infrastructure tools to evaluate the performance of our data Intelligence products. Strong problem-solving skills and effective communication are crucial for success in this role.
Minimum Qualifications
Bachelor's or Master's degree in Computer Science or a related technical field or equivalent experience
5+ years of industry experience optimizing for CPU, Memory and Latency issues
3+ years of industry experience using profiling/statistics/visualization tools relevant to performance measurement and analysis
Strong proficiency in SQL, Scala, Python, or Java, CI/CD practices, version control and API integrations
Experience with performance testing tools used to track and assess application performance in various scenarios and configurations
Strong proficiency with large datasets' processing, extraction, analysis and reporting
Knowledge: data modeling, data infrastructure, analytics, problem solving, debugging, testing, writing and maintaining high quality code.
Ability to translating requirements into technical solution.
Preferred Qualifications
Experience in Kubernetes and related containerization technologies, such as Docker
Familiarity with cloud platforms (AWS, Azure, GCP) and data management and analytics tools like Snowflake, Databricks and Tableau.
Hands-on experience with big data technologies such as distributed querying(Trino), real-time analytics(OLAP)
Proficiency with database query and crafting curated datasets.
Excellent verbal and written communication skills
Familiarity with GenAI concepts like Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), prompt engineering, vector embeddings, and LLM fine-tuning
Background in micro-frontend architectures or modular front-end design patterns.
Familiar with in Git and CI/CD tools.
Works independently with minimal oversight, actively builds relationships, and contributes to a positive team environment.
Seeks new opportunities for growth, demonstrates a thorough understanding of technical concepts, exercises independence in problem-solving, and delivers impactful results at the team level.
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