Data Platform Engineer (Remote)

Paymentology

8h • Remote

About The Position

Paymentology is seeking a Data Platform Engineer to join their Data Engineering team. This is a greenfield opportunity focused on designing and implementing scalable data infrastructure, engineering robust data pipelines, and establishing observability. The role is critical in enabling reliable, high-performance, and secure data systems. The engineer will work closely with data engineers, analysts, and senior technical stakeholders to design, implement, and operate the foundations of the data stack, including cloud infrastructure, data pipelines, 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.

Requirements

• 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.

Nice To Haves

• Experience with real-time data processing (e.g., Kafka, Spark Streaming) and both SQL and NoSQL data storage solutions is an advantage.

Responsibilities

• 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.

Benefits

• Opportunity to work in a diverse, global team.
• Supportive, forward-thinking environment.
• Opportunity to contribute to meaningful work.
• Collaborate across markets and functions.
• Shape the future of a business with global reach and real impact.
• Equal opportunity employer committed to fostering a diverse and inclusive workplace.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed