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Staff Engineer, Data Engineering

Remote / Online - Candidates ideally in
Wilmington, Middlesex County, Massachusetts, 01887, USA
Listing for: Analog Devices, Inc.
Full Time, Part Time, Remote/Work from Home position
Listed on 2026-09-24
Job specializations:
  • Software Development
    Data Engineering
Salary/Wage Range or Industry Benchmark: 178547 - 209715 USD Yearly USD 178547.00 209715.00 YEAR
Job Description & How to Apply Below
## Staff Engineer, Data Engineering Apply:
US, MA, Wilmington:
Full time:
Posted Today:
R266553
** 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, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible.

Learn more at  and on Linked In and X.
*
* Employer:

** Analog Devices, Inc.

*
* Job Title:

** Staff Engineer, Data Engineering
** Job

Requisition :** .5 / R266553
*
* Job Location:

** Wilmington, Massachusetts
** Job Type:
** Full Time
** Rate of Pay:** $178,547 - $209,715 per year    
** Duties:*
* * Architect, design, develop, and maintain scalable and efficient big data pipelines, ETL (Extract, Transform, Load) processes, and real-time analytics frameworks to process battery data.
* Translate business objectives and requirements into functional specifications on data pipelines and manage and coordinate deliverables to both internal and external stakeholders.
* Identify and implement appropriate data storage and retrieval solutions based on business needs.
* Ensure data quality, integrity, and accuracy through data validation, cleansing, and transformation techniques.
* Deploy and support machine learning workflows and AI/ML models in production environments, collaborating with algorithm engineers to integrate model outputs into scalable data pipelines
* Stay up to date with emerging trends and technologies in the field of data engineering and AI/ML, and continuously evaluate and recommend improvements to data infrastructure, tools, and processes.

Partial telecommute benefit (up to 2 days/week work from home).

** Requirements:
** Must have a Master’s degree in Computer Science, Computer Engineering, Software Engineering, Data Engineering, or closely related technical discipline (willing to accept foreign education equivalent) and five (5) years of experience in the offered job or Staff Engineer, Data Engineering-related occupation. Position also requires at least (3) years of experience with each of the following:
* Demonstrated Expertise (DE) architecting, designing, developing, and maintaining scalable big data pipelines, ETL processes, and real-time analytics frameworks, including experience with cloud-based data infrastructure, AI/ML workflow integration, and data quality processes.
* DE utilizing programming languages such as Python and/or Spark programming to design and build scalable data pipelines for processing large-scale time-series data originating from laboratory or device-based systems.
* DE with analytics engineering and data warehousing, including dimensional and normalized data modeling, schema evolution, and relational and non-relational database design, utilizing tools such as DBT, Snowflake, Redshift, and open table formats including Apache Iceberg or Delta Lake to support scalable cloud-based analytical workloads.
* DE designing and deploying cloud-based data pipelines using storage, compute, data integration, and streaming services such as AWS (S3, EC2, Glue, Lambda, Kinesis).
* DE programming with big data frameworks and data integration tools, including Apache Kafka, Apache Spark, and workflow orchestration platforms (Airflow or Prefect), and proficiency with SQL and No

SQL databases to support batch and large-scale time-series data streaming.
* DE managing and deploying data pipeline infrastructure, including version control systems such as Git Hub, CI/CD…
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