Data Platform Engineer

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**Data Platform Engineer

Paymentology, Belgrade**

At Paymentology, we’re redefining what’s possible in the payments space. As the first truly global issuer-processor, we give banks and fintechs the technology and talent to launch and manage Mastercard and Visa cards at scale - across more than 60 countries.

What you get to do:

🌸Design and implement cloud-based data platform infrastructure using Infrastructure as Code (Terraform), with a strong focus on scalability, security, reliability, and cost-efficiency.

🌸Build and maintain CI/CD pipelines that automate data engineering workflows, data pipeline deployments, and infrastructure provisioning, ensuring faster deployment cycles and minimizing errors.

🌸Implement and operate observability solutions — integrating monitoring, logging, and metrics to ensure platform reliability, performance visibility, and fast incident response.

🌸Collaborate closely with data engineers and cross-functional teams to design and implement data pipelines, data models, and platform capabilities that meet performance and business requirements.

🌸Apply best practices for high availability, disaster recovery, security and cost optimization, while documenting infrastructure patterns, data architecture decisions, and operational procedures.

What it takes to succeed:

💦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.

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