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Senior Data Engineer (GCP)

Pay
Pay not listedSimilar roles state $127K–$190K
Work setting
Remote — work setting source
Listed location: Remote, United States
Read the full posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Design and build scalable batch and streaming data pipelines on GCP

  • Develop data models, schemas, and ETL processes in BigQuery and Cloud SQL

  • Optimize pipelines for performance, scalability, and cost

  • Own pipeline reliability, including monitoring, alerting, and root cause analysis

  • Prepare and expose data for ML and agentic AI use cases

From the employer’s posting
Design and build scalable data pipelines using GCP services like Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer
Develop, test, and maintain data models, schemas, and ETL (Extract, Transform, Load) processes using BigQuery, Cloud SQL, Spark, and Data Studio
Optimize data pipelines for performance, scalability, and cost efficiency
Own pipeline and data infrastructure reliability end-to-end — monitoring, alerting, troubleshooting, and root cause analysis
Prepare, model, and expose data for ML and agentic AI use cases
Apply at Stord

Posting record

Report an error

Open 4 monthsWe first saw this posting 123 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 6, 2026123 days ago
Recorded sightings
172
Last seen by us
Nov 6, 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

Pay

$127K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,163 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 123

Up longer than most. Similar jobs usually come down between day 6 and day 54.

Well past Stord’s usual: its jobs come down by about day 42.

From 11,418 similar postings that came down, and 5 of Stord’s. Coming down is not always a hire.

Stord is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
  • 25% of open jobs were reposted
Hiring record

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
  • BigQuery
  • Docker
  • GCP
  • Kubernetes
  • Spark
  • Terraform
  • Airflow
  • TensorFlow
Where the posting names them
- Hands-on ETL development and workflow orchestration using tools like Apache Airflow - Proficiency in Python and/or Spark for data processing and pipeline development - Experience with streaming data pipelines (Pub/Sub, Dataflow, or similar) as well as batch processing
- Design and build scalable data pipelines using GCP services like Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer, ingesting, processing, and storing large datasets from multiple sources - Develop, test, and maintain data models, schemas, and ETL (Extract, Transform, Load) processes using BigQuery, Cloud SQL, Spark, and Data Studio - Partner with stakeholders to understand business requirements and translate them into data infrastructure that actually solves the problem
- 5+ years of data engineering experience, including at least three years in a cloud environment (preferably GCP) - Expertise across GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL - Strong SQL, with real experience writing complex queries for data extraction and analysis
- Expertise across GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL - Strong SQL, with real experience writing complex queries for data extraction and analysis - Hands-on ETL development and workflow orchestration using tools like Apache Airflow
- Experience with ML infrastructure on GCP, such as AI Platform and TensorFlow - Familiarity with DevOps/MLOps practices — CI/CD, infrastructure as code (Terraform), and containerization (Kubernetes, Docker) on GCP - Experience with other data processing frameworks, such as Apache Spark
What You'll Own: - Design and build scalable data pipelines using GCP services like Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer, ingesting, processing, and storing large datasets from multiple sources - Develop, test, and maintain data models, schemas, and ETL (Extract, Transform, Load) processes using BigQuery, Cloud SQL, Spark, and Data Studio
What You'll Bring: - 5+ years of data engineering experience, including at least three years in a cloud environment (preferably GCP) - Expertise across GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL
- Bachelor's degree in computer science or a comparable field, or equivalent experience - GCP certification (Professional Data Engineer or Cloud Architect) - Experience with ML infrastructure on GCP, such as AI Platform and TensorFlow
- Familiarity with DevOps/MLOps practices — CI/CD, infrastructure as code (Terraform), and containerization (Kubernetes, Docker) on GCP - Experience with other data processing frameworks, such as Apache Spark - A background in logistics, supply chain, 3PL, or warehouse/fulfillment technology
- Strong SQL, with real experience writing complex queries for data extraction and analysis - Hands-on ETL development and workflow orchestration using tools like Apache Airflow - Proficiency in Python and/or Spark for data processing and pipeline development
- GCP certification (Professional Data Engineer or Cloud Architect) - Experience with ML infrastructure on GCP, such as AI Platform and TensorFlow - Familiarity with DevOps/MLOps practices — CI/CD, infrastructure as code (Terraform), and containerization (Kubernetes, Docker) on GCP

Your next step

Complete your application on stord.wd503.myworkdayjobs.com. The employer’s form will show what is required.

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Already applied? Track this application

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.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,082.
August 17Last week

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

View original posting ↗

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission.

By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale.

With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord’s end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order.

Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.

Stord runs on data - every pallet moved, every order fulfilled, and every model our AI team ships depends on data that's fast, clean, and easy to find. As our Senior Data Engineer, you'll own that ecosystem: designing, building, and maintaining the pipelines and infrastructure that turn raw operational data into something the whole business can act on. You'll work closely with data scientists, analysts, and software engineers in a cloud-native environment, building for where Stord is headed, not just where it's been.

We move over $10 billion in commerce a year across fulfillment, warehousing, and supply chain software. You'll build the infrastructure that turns that volume into reliable, governed, ML-ready data - including the foundations our agentic AI tooling runs on.

What You'll Own:

  • Design and build scalable data pipelines using GCP services like Cloud Dataflow, Cloud Pub/Sub, Data Stream, Spark, and Cloud Composer, ingesting, processing, and storing large datasets from multiple sources

  • Develop, test, and maintain data models, schemas, and ETL (Extract, Transform, Load) processes using BigQuery, Cloud SQL, Spark, and Data Studio

  • Partner with stakeholders to understand business requirements and translate them into data infrastructure that actually solves the problem

  • Optimize data pipelines for performance, scalability, and cost efficiency, using GCP-native tools such as Dataproc and Bigtable

  • Ensure data quality, integrity, and security by building validation processes and enforcing data governance, access control, and security best practices

  • Automate workflows using Cloud Composer so pipelines run reliably and on schedule, not by accident

  • Own pipeline and data infrastructure reliability end-to-end — monitoring, alerting, troubleshooting, and root cause analysis — partnering with SRE and Infrastructure on shared GCP resources (compute, storage, network) rather than handing reliability off to someone else

  • Prepare, model, and expose data for ML and agentic AI use cases, including the governed data pipelines Stord's AI tooling queries in production

  • Mentor the broader data team as a senior technical voice on pipeline design and data infrastructure standards

  • Stay ahead of GCP's roadmap and emerging best practices, and put what you learn back into the platform

What You'll Bring:

  • 5+ years of data engineering experience, including at least three years in a cloud environment (preferably GCP)

  • Expertise across GCP services: BigQuery, Dataflow, Pub/Sub, Cloud Composer, Cloud Storage, Cloud Functions, and Cloud SQL

  • Strong SQL, with real experience writing complex queries for data extraction and analysis

  • Hands-on ETL development and workflow orchestration using tools like Apache Airflow

  • Proficiency in Python and/or Spark for data processing and pipeline development

  • Experience with streaming data pipelines (Pub/Sub, Dataflow, or similar) as well as batch processing

  • A solid grasp of data warehousing concepts, large datasets, and query optimization

  • Working knowledge of data governance, security, and compliance in a cloud environment

  • Understanding of ML concepts and data preparation for ML applications, with interest in agentic AI tooling a must

  • Strong analytical, problem-solving, and troubleshooting instincts, with real attention to detail

  • Clear, confident communication and the ability to collaborate across teams

Nice to Haves:

  • Bachelor's degree in computer science or a comparable field, or equivalent experience

  • GCP certification (Professional Data Engineer or Cloud Architect)

  • Experience with ML infrastructure on GCP, such as AI Platform and TensorFlow

  • Familiarity with DevOps/MLOps practices — CI/CD, infrastructure as code (Terraform), and containerization (Kubernetes, Docker) on GCP

  • Experience with other data processing frameworks, such as Apache Spark

  • A background in logistics, supply chain, 3PL, or warehouse/fulfillment technology

  • Experience working on a distributed team

Source details

View original posting ↗

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Remote, United States

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