Data Platform Engineer
Shift4
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 evolvesThis 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 wayOperate, tune, and scale the ECS/SQS‑based ingestion pipelines from Aurora MySQL into Snowflake: task sizing, autoscaling, consumer concurrency, batching, retries, and dead‑letter handlingOwn pipeline reliability: define SLOs for freshness and lag, build alerting and dashboards, lead incident response and root‑cause analysis for pipeline failuresBuild and maintain infrastructure as code, deployment automation, and CI/CD for pipeline servicesContinuously 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 teamsApply data‑quality and security controls appropriate for PCI‑compliant or payment‑handling environments: encryption, secrets handling, least‑privilege access, audit trailsProactively explore and apply AI tools to improve efficiency across the pipeline lifecycle (development, testing, runbooks, and documentation)Benefits
Wellness programs, including mental health resourcesOpportunities for career growth, skill-building, and advancementHappy hours, office celebrations, and well‑being initiativesPaid time off for relaxation and quality time with loved onesFlexible work schedules empower you to manage your commitments effectivelyVarious paid leave programs, including sick leave, parental leave, and more to support life’s important momentsEmployee‑nominated “Top Gun Program” to recognize exceptional individualsObservability and alerting for pipeline health and lag using Prometheus/Grafana, CloudWatch, Datadog, or the Elastic StackPassion for automation, performance, and clean system designDeep 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 side5+ years in platform, infrastructure, or DevOps roles supporting data‑intensive systems in productionExperience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring)Enough Python to read, debug, and instrument worker codeProven track record tuning message‑driven workloads: consumer concurrency, backpressure, retries, idempotency, throughput versus costInfrastructure as code with Terraform/Ansible, containerization with Docker, and CI/CD pipelinesCDC tooling (Debezium, AWS DMS) and MySQL Binlog replicationElastic Stack or time‑series database (Prometheus, InfluxDB) administrationMessage brokers beyond SQS: Apache Kafka/Confluent, RabbitMQExperience in a PCI or otherwise regulated environmentPayments or fintech domain knowledge
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Wellness programs, including mental health resourcesOpportunities for career growth, skill-building, and advancementHappy hours, office celebrations, and well‑being initiativesPaid time off for relaxation and quality time with loved onesFlexible work schedules empower you to manage your commitments effectivelyVarious paid leave programs, including sick leave, parental leave, and more to support life’s important momentsEmployee‑nominated “Top Gun Program” to recognize exceptional individualsObservability and alerting for pipeline health and lag using Prometheus/Grafana, CloudWatch, Datadog, or the Elastic StackPassion for automation, performance, and clean system designDeep 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 side5+ years in platform, infrastructure, or DevOps roles supporting data‑intensive systems in productionExperience operating pipelines into Snowflake from the ingestion side (Snowpipe/COPY, stages, load monitoring)Enough Python to read, debug, and instrument worker codeProven track record tuning message‑driven workloads: consumer concurrency, backpressure, retries, idempotency, throughput versus costInfrastructure as code with Terraform/Ansible, containerization with Docker, and CI/CD pipelinesCDC tooling (Debezium, AWS DMS) and MySQL Binlog replicationElastic Stack or time‑series database (Prometheus, InfluxDB) administrationMessage brokers beyond SQS: Apache Kafka/Confluent, RabbitMQExperience in a PCI or otherwise regulated environmentPayments or fintech domain knowledge
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