Data Platform Engineer

Paymentology

Data Platform Engineer at Paymentology designing and implementing scalable cloud data infrastructure. Focused on building a modern data platform and collaborating with engineering teams.

Posted 4/28/2026full-timeRemote • CzechiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSBigQueryCloudGoogle Cloud PlatformKafkaKubernetesNoSQLPythonSparkSQLTerraform

About the role

Key responsibilities & impact

Design and implement cloud-based data platform infrastructure using Infrastructure as Code (Terraform)
Build and maintain CI/CD pipelines that automate data engineering workflows, data pipeline deployments, and infrastructure provisioning
Implement and operate observability solutions - integrating monitoring, logging, and metrics
Collaborate closely with data engineers and cross-functional teams to design and implement data pipelines, data models, and platform capabilities
Apply best practices for high availability, disaster recovery, security and cost optimization, while documenting infrastructure patterns, data architecture decisions, and operational procedures

Requirements

What you’ll need

3-5 years of hands-on experience in Data Engineering, Platform Engineering, or DataOps roles
Proven track record in designing and implementing reliable, scalable data platforms and data infrastructure - not just supporting, but owning end-to-end delivery
Hands-on experience with modern data engineering tools such as dbt, Apache Airflow or Apache Kafka is required
Hands-on proficiency with Infrastructure as Code (Terraform) and cloud architecture patterns on AWS or GCP
Deep experience with AWS or GCP, including data storage and processing services (e.g., BigQuery, Snowflake, S3, Redshift)
Practical experience with Kubernetes and containerised workloads for orchestrating data platform services
Experience implementing observability stacks for data platform monitoring, logging, metrics, and alerting
Strong programming skills in Python, SQL, and Bash to build data pipelines, automate workflows, and perform data processing
Excellent problem-solving skills and the ability to work effectively in a collaborative, fully remote environment
A strong inclination to deepen expertise in data architecture, data modelling, and MLOps capabilities
Experience with real-time data processing (e.g., Kafka, Spark Streaming) and both SQL and NoSQL data storage solutions is an advantage.

Benefits

Comp & perks

Diverse, global team that is genuinely committed to making a positive impact through work
Freedom to grow in a supportive, forward-thinking environment

ATS Keywords

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Hard Skills & Tools

Data EngineeringPlatform EngineeringDataOpsInfrastructure as CodeTerraformdbtApache AirflowApache KafkaKubernetesPython

Soft Skills

problem-solvingcollaborationremote work