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Cupertino, California - USD Full Time Posted: Friday, 8 November 2019
Siri Search and Knowledge - Analytics Platform Engineer
Santa Clara Valley (Cupertino),California,United States
Machine Learning and AI
  • 2+ years of experience as a Software Engineer
  • Excellent analytical and problem solving skills
  • Proficiency in one of the following languages: Python, Go, Java, C++ Desire to contribute to a nascent data ecosystem and to build a strong data toolset for the company
  • Experience with large, complex, highly dimensional data sets; hands-on experience with SQL/HQL
  • Experience with Hadoop, Hive, and/or Impala is a plus
  • Experience applying algorithms to understand real-world data (classification, anomaly detection, etc.) is a plus
  • Phenomenal interpersonal skills required
You are someone with at least a few of the following traits: - Is excited about digging into massive petabyte-scale semi-structured datasets - Has experience in distributed systems, database internals, or performance analysis - Has experience with dimensional analytics platforms (OLAP) and data visualization systems - Has experience with A/B testing infrastructure, machine learning infrastructure - Has experience with map/reduce and big data frameworks, such as Hadoop, Spark, Dask - Has a deep understanding of polyglot data persistence (relational, key/value, document, column, graph, data warehousing) - Strong dedication to code quality, automation, and operational excellence: unit and integration tests, linting, documentation, etc What you will do: - Develop software to process, transform, and analyze data to identify signals from the billions of events we collect every day. - Design and build abstractions that hide the complexity of the underlying big data stack (HDFS, Hadoop, Hive, Impala, Spark, Kafka, Parquet, etc) and allow partners to focus on their strengths: product, data modeling, data analysis, search, information retrieval, and machine learning. - Act as the source of truth for our most fundamental data - such as search activity and content - as well as our core metrics across a variety of products. - Surface datasets in near-real-time to mission critical products and business applications throughout the company, providing the signal that feeds our machine learning algorithms as well as our daily product-defining decisions. - Empower dozens of engineering teams, hundreds of co-workers, and hundreds of millions of users to dream of new possibilities for the product. - Build scalable Back End services and tools to help partners implement, deploy and analyze data assets with a high level of autonomy and limited friction. - Optimize end-to-end workflows of data users (crafting libraries, providing abstractions to define jobs, scheduling data pipelines, managing access data assets, etc). - Provide transparency into our data flows (comprehensive view of sources, transformations, sinks, data lineage). - Automate and handle lifecycle of datasets (schema evolution, metadata store, backfill management, deprecation, migration). - Improve the quality and reliability of the pipelines (monitoring, retry, failure detection). - Supply reusable Back End abstractions to ingest or access data sets (batch, streaming, and low latency APIs). - Choose the right tools for the job, whether that means gluing things together with Bash, prototyping in Python, productizing in Java/Go, or scheduling with Groovy.
Education & Experience
BS in Computer Science, Mathematics, Statistics, or a related field, or equivalent industry experience.
Additional Requirements
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Cupertino, California, United States of America
11/8/2019 11:46:08 AM

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