Data Platform Engineer
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Posting language
- English
- Posted
Original job description
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)
- 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
- 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
More about this job
Responsibilities
Operate, optimize, and scale AWS-based ingestion pipelines that move data from Aurora MySQL into Snowflake, improving throughput, reliability, and cost efficiency. Build deployment and infrastructure automation, establish pipeline monitoring and incident practices, onboard new sources and consumers, and apply appropriate security and data-quality controls.
Requirements
Requires at least five years in platform, infrastructure, or DevOps roles supporting production data-intensive systems, with hands-on AWS experience across ECS/Fargate, SQS, S3, IAM, CloudWatch, and Aurora/RDS. Candidates should have experience with Snowflake ingestion, message-driven workload tuning, infrastructure as code, Docker, CI/CD, observability, and enough Python to debug and instrument worker code.
Skills
- AWS ECS/Fargate
- Amazon SQS
- Snowflake Ingestion
- Aurora MySQL
- Infrastructure as Code
- Terraform
- Ansible
- Docker
- CI/CD
- Pipeline Observability
- Prometheus/Grafana
- CloudWatch
- Python
- Message-Driven Workloads
- Data Pipeline Reliability
- PCI Security Controls
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Data & Analytics
- Software
- Engineering
- Finance & Accounting
Keywords
- AWS
- Amazon ECS
- AWS Fargate
- Amazon SQS
- Amazon S3
- IAM
- CloudWatch
- Aurora MySQL
- Amazon RDS
- Snowflake
- Snowpipe
- COPY
- Terraform
- Ansible
- Docker
- CI/CD
- Python
- Prometheus
- Grafana
- Datadog
- Elastic Stack
- Debezium
- AWS DMS
- MySQL Binlog Replication
- Apache Kafka
- Confluent
- RabbitMQ
- Change Data Capture
- PCI Compliance
- Payment Processing