Pay
Higher than most similar jobs
$179K–$210K against $127K–$190K, the middle half of what similar US postings state.
From 2,159 postings in the last year. Stated ranges, not salaries paid.
Staff Engineer, Data Engineering
US, MA, Wilmington
Live, first seen by us 47 days ago- Pay
$178,547–209,715/year — pay source
Job Type: Full Time Rate of Pay: $178,547 - $209,715 per year Duties:
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Job Location: Wilmington, Massachusetts Job Type: Full Time Rate of Pay: $178,547 - $209,715 per year
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingArchitect, build and maintain scalable big data pipelines and ETL processes for battery data
Turn business objectives into functional pipeline specifications and coordinate deliverables
Choose data storage and retrieval solutions based on business needs
Ensure data quality through validation, cleansing and transformation
Deploy and support ML and AI models in production data pipelines
From the employer’s posting
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
Education & alternatives
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:
About Analog
(NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge.
In the employer’s words · Read in context
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 22, 202647 days ago
- Recorded sightings
- 137
- Last seen by us
- Nov 8, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 47
Similar jobs usually come down between day 6 and day 54.
At Analog, jobs usually come down by about day 54.
From 11,581 similar postings that came down, and 51 of Analog’s. Coming down is not always a hire.
Analog is hiring
17 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring has slowed
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- dbt
- Delta Lake
- Docker
- Iceberg
- Kafka
- Kubernetes
- NoSQL
- Prefect
- Redshift
- S3
- SageMaker
- Snowflake
- Spark
- Airflow
Where the posting names them
- 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 NoSQL databases to support batch and large-scale time-series data streaming. - DE managing and deploying data pipeline infrastructure, including version control systems such as GitHub, CI/CD automation, containerization and orchestration using Docker and Kubernetes, and integrating ML model training and deployment workflows using AWS SageMaker.
- 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 NoSQL databases to support batch and large-scale time-series data streaming.
- 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 NoSQL databases to support batch and large-scale time-series data streaming. - DE managing and deploying data pipeline infrastructure, including version control systems such as GitHub, CI/CD automation, containerization and orchestration using Docker and Kubernetes, and integrating ML model training and deployment workflows using AWS SageMaker. - DE collaborating with cross-functional teams including algorithm engineers, hardware or device engineers, and domain experts to gather data requirements, translate business and engineering objectives into functional pipeline specifications, and manage and coordinate deliverables across both internal and external stakeholders.
- 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).
Your next step
Complete your application on analogdevices.wd1.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
About Analog
- People
- About 24,500 in 2025, up 2% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as ADI.
- H-1B visas
- 83 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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 www.analog.com and on LinkedIn and X.
Employer: Analog Devices, Inc.
Job Title: Staff Engineer, Data Engineering
Job Requisition: 1010.1330.5 / 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 NoSQL databases to support batch and large-scale time-series data streaming.
- DE managing and deploying data pipeline infrastructure, including version control systems such as GitHub, CI/CD automation, containerization and orchestration using Docker and Kubernetes, and integrating ML model training and deployment workflows using AWS SageMaker.
- DE collaborating with cross-functional teams including algorithm engineers, hardware or device engineers, and domain experts to gather data requirements, translate business and engineering objectives into functional pipeline specifications, and manage and coordinate deliverables across both internal and external stakeholders.
Partial telecommute benefit (up to 2 days/week work from home).
Contact: Eligible for employee referral program. Apply online at https://www.analog.com/en/careers.html and Reference Position Number: R266553
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/Days
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Job Type: Full Time Rate of Pay: $178,547 - $209,715 per year Duties:
- Location & working pattern
US, MA, Wilmington
Working pattern and location restrictions need checking in the full posting.
- Work authorization
Contact: Eligible for employee referral program. Apply online at https://www.analog.com/en/careers.html and Reference Position Number: R266553 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.