Data Platform Engineer

Shift4 Corporation
Upper Saucon Township, PA, United States
22 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Audit Trail Databases Continuous Integration Data Infrastructure Software Debugging DevOps Elasticsearch Identity and Access Management Python (Programming Language)
+21 more
Message Broker MySQL RabbitMQ Ansible Prometheus Datadog Data Ingestion Autoscaling Snowflake Grafana Debezium Infrastructure Automation Frameworks Influxdb Deployment Automation AWS Fargate Apache Kafka Cloudwatch Amazon Simple Queue Service (SQS) Terraform Docker Confluent

Job description

  • 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)

Requirements

  • 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

About the company

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 looking for a Data Platform Engineer to join our Data Platform team and own the pipelines that move data from our production systems into the analytics warehouse. At present, multiple ECS services and SQS queues handle the replication of Aurora MySQL into Snowflake. Tomorrow, it will include more sources and more consumers. This is a hands-on infrastructure role focused on the throughput, reliability, sizing, cost, and observability of the pipes themselves. Data modeling, warehouse cost management, and business transformation logic are owned by other teams. You make sure the data gets there, on time, every time, while embracing the Shift4 way.

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