Data Platform Engineer

Paymentology View all jobs

  • Valletta, Malta Island
  • Permanent
  • Full-time
  • 2 months ago
  • Apply easily
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.Our advanced, multi-cloud platform delivers real-time data, unmatched scalability, and the flexibility of shared or dedicated processing instances. It's this global reach and innovation that sets us apart.We're looking for a Data Platform Engineer to join our Data Engineering team and help build a modern data platform from the ground up. This is a greenfield opportunity focused on designing and implementing scalable data infrastructure, engineering robust data pipelines, and establishing observability, playing a critical role in enabling reliable, high-performance, and secure data systems.You'll work closely with data engineers, analysts, and senior technical stakeholders to design, implement, and operate the foundations of our data stack — from cloud infrastructure and data pipelines to storage and processing layers. This role is ideal for an experienced engineer with strong data platform and cloud infrastructure expertise who thrives in a high-impact, global fintech environment.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 you can look forward to::At Paymentology, it's not just about building great payment technology, it's about building a company where people feel they belong and their work matters. You'll be part of a diverse, global team that's genuinely committed to making a positive impact through what we do. Whether you're working across time zones or getting involved in initiatives that support local communities, you'll find real purpose in your work — and the freedom to grow in a supportive, forward-thinking environment.Travel:
< 10%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.
  • Experience with real-time data processing (e.g., Kafka, Spark Streaming) and both SQL and NoSQL data storage solutions is an advantage.


Paymentology

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