About Analog Devices
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 $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).
Join our innovative team at the Analog Garage, Analog Devices' internal innovation lab, where collaboration, creativity, and cutting-edge technology converge.
We're a dynamic group of software engineers, hardware engineers, scientists, and business leaders passionate about
solving complex problems and developing groundbreaking solutions.
Our Mission
As part of our Platforms and Systems team, you'll tackle exciting challenges in:
Renewable Energy: Harness innovation for a sustainable future
Advanced Biotechnology: Unlock new possibilities for human health
Robotics: Revolutionize industries with intelligent machines
Your Role
We are seeking a Senior Data Engineer to join our small but highly impactful DevOps and Data Engineering team within our larger R&D organization. As the first dedicated Data Engineer on the team, you will play a pivotal role in shaping our data strategy, driving technical architecture, and laying the foundation for scalable and maintainable data systems. You’ll have the opportunity to mentor and coach colleagues across the organization, collaborate with software engineers, DevOps, and AI/ML engineers, and lead the implementation of best practices for data engineering.
This role is ideal for someone who thrives in a hybrid environment—where data originates from diverse sources including IoT devices, robotics, lab sensors, and other systems—and is passionate about building reliable pipelines that feed cloud-based analytics and decision-making. You’ll need to be excited by the idea of leaning into and growing your DevOps skillset as you will be a contributing towards the DevOps platform and function.
Responsibilities
Design and implement scalable, reliable, and maintainable data pipelines and architectures that ingest, transform, and store data from a variety of on-premises and cloud sources.
Define and drive the organization’s data strategy, including data modeling, governance, and infrastructure.
Collaborate with software engineers, DevOps, and R&D teams to build systems that enable robust data collection, processing, and analysis.
Develop tooling, frameworks, and libraries that accelerate data engineering workflows and promote reusability.
Establish best practices and standards for data engineering within the organization (e.g., testing, documentation, deployment).
Mentor and coach team members and stakeholders on data engineering concepts and practices.
Identify opportunities for process automation, data quality improvements, and performance optimization.
Evaluate and recommend appropriate technologies and platforms to support evolving data needs.
Required Skills
Strong proficiency in Python, SQL, and at least one modern data pipeline orchestration tool (e.g., Airflow, Prefect, Dagster).
Deep experience designing and building data pipelines (ETL/ELT) and data processing frameworks.
Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and their data-related services (e.g., S3, Redshift, BigQuery).
Experience working in hybrid environments, integrating data from on-premise systems, IoT devices, robotics, lab sensors, etc., into cloud-based architectures.
Knowledge of data modeling concepts (e.g., star/snowflake schema, normalized/denormalized models).
Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).
Strong problem-solving skills and the ability to translate complex business needs into technical solutions.
Experience with streaming data technologies (e.g., Kafka, Kinesis, Spark Structured Streaming).
Strong experience with Terraform, Kubernetes, and Helm.
Nice-to-Have Skills
Familiarity with Spark, dbt, Iceberg
Familiarity with ML workflows
Experience with CI/CD practices for data pipelines.
Experience mentoring engineers or leading small teams.
Prior experience in R&D environments or working with highly cross-functional teams.
For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.
Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.
EEO is the Law: Notice of Applicant Rights Under the Law.
Job Req Type: ExperiencedRequired Travel: No
Shift Type: 1st Shift/DaysThe expected wage range for a new hire into this position is $108,800 to $149,600.
Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.
This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.
This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.
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