Be an early applicantLess than 25 applicants

Company

Applied Materials · 4 hours ago

Data Engineer

Texas, United States

Full-time

Remote

Mid, Senior Level

$132K/yr - $182K/yr

5+ years exp

Maximize your interview chances

ElectronicsManufacturing

H1B Sponsor Likely

Insider Connection @Applied Materials

Discover valuable connections within the company who might provide insights and potential referrals.
Get 3x more responses when you reach out via email instead of LinkedIn.

Responsibilities

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.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

SQLBig DataData Pipeline ArchitectureData TransformationPythonHadoopSparkKafkaPostgresCassandraMongoDBClickHouseAzkabanLuigiAirflowEC2EMRRDSRedshiftAzure ServicesStormSpark-StreamingJavaC++ScalaProject Management

Required

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.

Experience with big data tools: Hadoop, Spark, Kafka, etc.

Experience with relational SQL and NoSQL databases, including Postgres, Cassandra, MongoDB, ClickHouse.

Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.

Experience with cloud services: such as EC2, EMR, RDS, Redshift, Azure services.

Experience with stream-processing systems: Storm, Spark-Streaming, etc.

Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Candidate with 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.

Bachelor's Degree

Benefits

Comprehensive benefits package

Participation in a bonus and a stock award program

Company

Applied Materials

Glassdoor

4.0

Applied Materials is a semiconductor and display equipment company that offers materials engineering solutions.

Founded in 1967

Santa Clara, California, USA

10,001+ employees

http://www.appliedmaterials.com

H1B Sponsorship

Applied Materials has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2023 (280)

2022 (405)

2021 (478)

2020 (378)