Applied Materials Data Science Engineer IV (E4) in O'fallon, Missouri
Data Science Engineer
Data Science Engineer will be responsible for expanding and optimizing APF data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The Data Engineer will support our software developers, database architects, and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives. This position can be remote and located anywhere in the US or Asia.
Create and maintain optimal data pipeline architecture
Assemble large, complex data sets that meet functional / non-functional business requirements.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Product management, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency and workload management.
A successful history of manipulating, processing and extracting value from large disconnected datasets.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Strong project management and organizational skills.
Experience supporting and working with cross-functional teams in a dynamic environment.
5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
They should also have experience using the following software/tools:
big data tools: Hadoop, Spark, Kafka, etc.
relational SQL and NoSQL databases, including Postgres and Cassandra.
data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
AWS cloud services: EC2, EMR, RDS, Redshift
stream-processing systems: Storm, Spark-Streaming, etc.
object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Years of Experience:
4 - 7 Years
Yes, 25% of the Time
Applied Materials is committed to diversity in its workforce including Equal Employment Opportunity for Minorities, Females, Protected Veterans and Individuals with Disabilities.
Applied Materials is the leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. Our expertise in modifying materials at atomic levels and on an industrial scale enables customers to transform possibilities into reality. At Applied Materials, our innovations make possible the technology shaping the future.