Analog Devices
DevOps Engineer, Data Engineering
Analog Devices, San Jose, California, United States, 95199
Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $12 billion in FY22 and approximately 25,000 people globally working alongside 125,000 global customers, ADI ensures today’s innovators stay Ahead of What’s Possible.
Primary Location(s):
San Jose, CA or Boston, MA
Secondary Locations(s):
Durham, NC, Dallas TX or Beaverton, OR
Responsibilities
As a DevOps Engineer for Data Engineering, you help build, deliver, and optimize software and infrastructure to enable a modern data engineering tech stack.Play a key role in contributing to the data engineering DevOps processes by establishing and maintaining the necessary cloud infrastructure to support our global operations.Build end-to-end data pipelines and integrate them into product and business system workflows.Lead and own the continuous integration processes of our data pipelines that are built, tested, and released on various data orchestration frameworks (Airflow, Dagster, etc.).Provide production support to resolve critical data pipeline and application issues, mitigating or minimizing any impact on data products and downstream analytics tools.Propose, implement, and deploy efficient and scalable DevOps solutions to allow our fast-growing team to release software more frequently while maintaining high-quality and top performance.Build data profiling, monitoring, and ETL workflows, joining together heterogeneous sources including business data, analytics data, and product data.Automate away recurring tasks while employing and advancing best in class software development practices.Qualifications
5+ years of experience in software engineering, including 3+ years in data engineering and DevOps roles.Degree in Computer Science or a related field.Strong system level programming skills (Python, shell scripting, etc.) and familiarity with Linux system administration.Hands-on experience with infrastructure engineering, infrastructure-as-code, modern DevOps processes, CI/CD, and GitHub.Experience with developing, implementing, and optimizing data orchestration systems, such as AirFlow or Dagster.Ability to work with and manage cloud data technologies, such as Kafka, ElasticSearch, Terraform, etc.Excellent debugging and optimization skills.
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Primary Location(s):
San Jose, CA or Boston, MA
Secondary Locations(s):
Durham, NC, Dallas TX or Beaverton, OR
Responsibilities
As a DevOps Engineer for Data Engineering, you help build, deliver, and optimize software and infrastructure to enable a modern data engineering tech stack.Play a key role in contributing to the data engineering DevOps processes by establishing and maintaining the necessary cloud infrastructure to support our global operations.Build end-to-end data pipelines and integrate them into product and business system workflows.Lead and own the continuous integration processes of our data pipelines that are built, tested, and released on various data orchestration frameworks (Airflow, Dagster, etc.).Provide production support to resolve critical data pipeline and application issues, mitigating or minimizing any impact on data products and downstream analytics tools.Propose, implement, and deploy efficient and scalable DevOps solutions to allow our fast-growing team to release software more frequently while maintaining high-quality and top performance.Build data profiling, monitoring, and ETL workflows, joining together heterogeneous sources including business data, analytics data, and product data.Automate away recurring tasks while employing and advancing best in class software development practices.Qualifications
5+ years of experience in software engineering, including 3+ years in data engineering and DevOps roles.Degree in Computer Science or a related field.Strong system level programming skills (Python, shell scripting, etc.) and familiarity with Linux system administration.Hands-on experience with infrastructure engineering, infrastructure-as-code, modern DevOps processes, CI/CD, and GitHub.Experience with developing, implementing, and optimizing data orchestration systems, such as AirFlow or Dagster.Ability to work with and manage cloud data technologies, such as Kafka, ElasticSearch, Terraform, etc.Excellent debugging and optimization skills.
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