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Day 20
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From 11,283 similar postings that came down. Coming down is not always a hire.
Data Platform Engineer
Toronto, ON Office
Live, first seen by us 20 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- 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 postingTune ECS and SQS ingestion pipelines for sizing, autoscaling, concurrency, batching, and retries
Define freshness and lag SLOs, build alerts and dashboards, and lead pipeline incident response
Build and maintain infrastructure as code and CI/CD for pipeline services
Benchmark throughput versus cost across ECS, SQS, and Snowflake ingestion
Onboard new data sources and consumers with application, data, and analytics teams
From the employer’s posting
Operate, tune, and scale the ECS/SQS-based ingestion pipelines from Aurora MySQL into Snowflake: task sizing, autoscaling, consumer concurrency, batching, retries, and dead-letter handling
define SLOs for freshness and lag, build alerting and dashboards, lead incident response and root-cause analysis for pipeline failures
Build and maintain infrastructure as code, deployment automation, and CI/CD for pipeline services
Continuously benchmark and tune throughput versus cost across ECS, SQS, and Snowflake ingestion (Snowpipe/COPY, stages)
Onboard new sources and consumers to the platform in partnership with application, data, and analytics teams
What you’ll bring
All qualificationsCore experience
- 5+ years in platform, infrastructure, or DevOps roles supporting data-intensive systems in production
- Experience in a PCI or otherwise regulated environment
- Experience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring)
Qualification wording
5+ years in platform, infrastructure, or DevOps roles supporting data-intensive systems in production
Experience in a PCI or otherwise regulated environment
Experience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring)
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 16, 202620 days ago
- Recorded sightings
- 28
- 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
Shift4 is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee 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
- AWS
- Datadog
- Docker
- Grafana
- Kafka
- MySQL
- S3
- Snowflake
- Terraform
Where the posting names them
- Observability and alerting for pipeline health and lag using Prometheus/Grafana, CloudWatch, Datadog, or the Elastic Stack - Enough Python to read, debug, and instrument worker code - Passion for automation, performance, and clean system design
- 5+ years in platform, infrastructure, or DevOps roles supporting data-intensive systems in production - Deep hands-on AWS experience: ECS/Fargate (task sizing, autoscaling, deployments), SQS (throughput, DLQs, visibility timeouts, batching), S3, IAM, CloudWatch, and Aurora/RDS from the operator side - Proven track record tuning message-driven workloads: consumer concurrency, backpressure, retries, idempotency, throughput versus cost
Nice to have - CDC tooling (Debezium, AWS DMS) and MySQL Binlog replication - Message brokers beyond SQS: Apache Kafka/Confluent, RabbitMQ
- Infrastructure as code with Terraform/Ansible, containerization with Docker, and CI/CD pipelines - Observability and alerting for pipeline health and lag using Prometheus/Grafana, CloudWatch, Datadog, or the Elastic Stack - Enough Python to read, debug, and instrument worker code
- Experience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring) - Infrastructure as code with Terraform/Ansible, containerization with Docker, and CI/CD pipelines - Observability and alerting for pipeline health and lag using Prometheus/Grafana, CloudWatch, Datadog, or the Elastic Stack
- CDC tooling (Debezium, AWS DMS) and MySQL Binlog replication - Message brokers beyond SQS: Apache Kafka/Confluent, RabbitMQ - Elastic Stack or time-series database (Prometheus, InfluxDB) administration
Shift4 (NYSE: FOUR) is boldly redefining commerce by simplifying complex payments ecosystems across the world. As the leader in commerce-enabling technology, Shift4 powers billions of transactions annually for hundreds of thousands of businesses in virtually every industry. For more information, visit www.shift4.com. Shift4 is seeking a Data Platform Engineer to join our Data Platform team and build, maintain, and optimize the pipelines that move data from our production systems into our analytics warehouse. Today, our infrastructure uses Amazon ECS services and SQS queues to replicate data from Aurora MySQL into Snowflake, with plans to expand to additional data sources and consumers as our platform evolves. This is a hands-on infrastructure engineering role focused on pipeline performance, reliability, scalability, resource optimization, cost efficiency, and observability. You will help ensure data is delivered accurately, reliably, and on time as our data platform grows. Data modeling, warehouse cost management, and business transformation logic are managed by partner teams, allowing you to focus on the infrastructure and systems that power our data ecosystem—all while embracing the Shift4 way.
Responsibilities - Operate, tune, and scale the ECS/SQS-based ingestion pipelines from Aurora MySQL into Snowflake: task sizing, autoscaling, consumer concurrency, batching, retries, and dead-letter handling - Own pipeline reliability: define SLOs for freshness and lag, build alerting and dashboards, lead incident response and root-cause analysis for pipeline failures
- Build and maintain infrastructure as code, deployment automation, and CI/CD for pipeline services - Continuously benchmark and tune throughput versus cost across ECS, SQS, and Snowflake ingestion (Snowpipe/COPY, stages) - Onboard new sources and consumers to the platform in partnership with application, data, and analytics teams
- Proven track record tuning message-driven workloads: consumer concurrency, backpressure, retries, idempotency, throughput versus cost - Experience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring) - Infrastructure as code with Terraform/Ansible, containerization with Docker, and CI/CD pipelines
Your next step
Complete your application on shift4payments.wd108.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
Has Shift4 posted this job before?
Yes. We’ve followed one other Data Platform Engineer job there since October 2026. It came down after 0 days.
About Shift4
- People
- About 6,300 in 2025, up 57% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as FOUR.
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
Shift4 (NYSE: FOUR) is boldly redefining commerce by simplifying complex payments ecosystems across the world. As the leader in commerce-enabling technology, Shift4 powers billions of transactions annually for hundreds of thousands of businesses in virtually every industry. For more information, visit www.shift4.com.
Shift4 is seeking a Data Platform Engineer to join our Data Platform team and build, maintain, and optimize the pipelines that move data from our production systems into our analytics warehouse. Today, our infrastructure uses Amazon ECS services and SQS queues to replicate data from Aurora MySQL into Snowflake, with plans to expand to additional data sources and consumers as our platform evolves.
This is a hands-on infrastructure engineering role focused on pipeline performance, reliability, scalability, resource optimization, cost efficiency, and observability. You will help ensure data is delivered accurately, reliably, and on time as our data platform grows. Data modeling, warehouse cost management, and business transformation logic are managed by partner teams, allowing you to focus on the infrastructure and systems that power our data ecosystem—all while embracing the Shift4 way.
Responsibilities
- Operate, tune, and scale the ECS/SQS-based ingestion pipelines from Aurora MySQL into Snowflake: task sizing, autoscaling, consumer concurrency, batching, retries, and dead-letter handling
- Own pipeline reliability: define SLOs for freshness and lag, build alerting and dashboards, lead incident response and root-cause analysis for pipeline failures
- Build and maintain infrastructure as code, deployment automation, and CI/CD for pipeline services
- Continuously benchmark and tune throughput versus cost across ECS, SQS, and Snowflake ingestion (Snowpipe/COPY, stages)
- Onboard new sources and consumers to the platform in partnership with application, data, and analytics teams
- Apply data-quality and security controls appropriate for PCI-compliant or payment-handling environments: encryption, secrets handling, least-privilege access, audit trails
- Proactively explore and apply AI tools to improve efficiency across the pipeline lifecycle (development, testing, runbooks, and documentation)
Qualifications
- 5+ years in platform, infrastructure, or DevOps roles supporting data-intensive systems in production
- Deep hands-on AWS experience: ECS/Fargate (task sizing, autoscaling, deployments), SQS (throughput, DLQs, visibility timeouts, batching), S3, IAM, CloudWatch, and Aurora/RDS from the operator side
- Proven track record tuning message-driven workloads: consumer concurrency, backpressure, retries, idempotency, throughput versus cost
- Experience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring)
- Infrastructure as code with Terraform/Ansible, containerization with Docker, and CI/CD pipelines
- Observability and alerting for pipeline health and lag using Prometheus/Grafana, CloudWatch, Datadog, or the Elastic Stack
- Enough Python to read, debug, and instrument worker code
- Passion for automation, performance, and clean system design
Nice to have
- CDC tooling (Debezium, AWS DMS) and MySQL Binlog replication
- Message brokers beyond SQS: Apache Kafka/Confluent, RabbitMQ
- Elastic Stack or time-series database (Prometheus, InfluxDB) administration
- Experience in a PCI or otherwise regulated environment
- Payments or fintech domain knowledge
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class.
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Toronto, ON Office
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