Senior Data Engineer, SWE Operations & Planning

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. The Engineering Operations and Planning team within Software Engineering (SWE) is looking for a data engineer to continue scaling and improving our existing data infrastructure, while also innovating on new tooling. This role is crafted to bring efficiency, process, and standardization to the organization by building scalable data pipelines and repositories that process, clean, and validate the integrity of the data from raw sources and prepare data for analysis and visualization with particular focus on historical repositories and change control.

Description

The successful candidate will have a proactive approach with the ability to work independently and collaboratively on a wide range of projects. In this role, you will work alongside a small but impactful team, collaborating with data analysts, software developers, project managers and other teams at Apple to understand requirements and translate them into scalable, reliable, and efficient data pipelines, and data processing workflows. - Responsible for architecting and implementing large scale systems and data pipelines with a focus on agility, interoperability, simplicity, and reusability - Apple business acumen, expertise and strategies into data modeling solutions - Utilize deep knowledge in infrastructure, warehousing, data protection, security, data collection, processing, modeling, and metadata management to build end-to-end solutions that also support metadata logging, anomaly detection, data cleaning, and transformation - Identify process improvements opportunities (tools, work streams, systems) and drive solutions from conception to implementation - Demonstrate and explain complex business processes, systems, and/or tools with a focus on the upstream/downstream impact and relationship between multiple functions and/or decisions - Identify and address issues in data design or integration - Discuss technical tradeoffs across the stack, including: system architecture, database design, API design and infrastructure

Minimum Qualifications

Bachelor’s Degree or equivalent experience in Computer Science, Engineering, Mathematics, Information Systems, Software Engineering, Data Science, Statistics or a related field 5+ years experience in architecting, designing, developing and maintaining large-scale ETL/ELT pipelines(batching and/or streaming) and data solutions that are optimized for performance and can handle data from various sources, structured or unstructured data. Deep expertise in Data Principles, Data Architecture (including documentation) & Data Modeling, Strong SQL skills. Strong problem solver with excellent organizational and time management skills, acute attention to detail, and capability of taking on loosely defined problems.

Preferred Qualifications

Experience with: Ruby, Rails, PostgreSQL, Snowflake, Kubernetes, Tableau or similar technologies. We believe great engineers are capable of learning new technologies, but experience in the above will be beneficial. Experience with enterprise resource planning (ERP) systems such as human resources information, real estate and development and/or finance systems Demonstrates a strong sense of professionalism; able to translate business requirements into forward-looking technical solutions and work autonomously on assignments while handling sensitive and confidential information with integrity and discretion. Proficiency in various data modeling techniques, such as ER, Hierarchical, Relational, or NoSQL modeling. Excellent design and development experience with SQL and NoSQL database, OLTP and OLAP databases Expertise in Java, Scala, Python, or Unix Shell scripting and dependency-driven job schedulers Experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects Familiarity with Apple technologies such as Xcode and Swift are a plus. Familiarity with other related fields, such as data science, machine learning, and artificial intelligence, to design solutions that can accommodate advanced analytics