Back to jobs

Staff Engineer, Data Engineering

US, MA, Wilmington

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

Before you apply

New graduates
Not stated
Work authorization
Not stated
Apply at Analog

What you’ll work on

Full posting
  • Architect, 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:

Tools in this posting

  • Python
  • SQL
  • AWS
  • dbt
  • Delta Lake
  • Docker
  • Iceberg
  • Kafka
  • Kubernetes
  • NoSQL
  • Prefect
  • Redshift
  • S3
  • SageMaker
  • Snowflake
  • Spark
  • Airflow
Source — Tool mentions in context
- 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).

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, 2026 · 42 days ago
Recorded sightings
132
Last seen by us
Nov 3, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on analogdevices.wd1.myworkdayjobs.com. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

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: Experienced

          

Required 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

View original posting ↗

Source notes

Source excerpts

Selected 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.

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.