Senior Data Engineer

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, Visa, and UnionPay 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 aSenior Data Engineerto architect and implement a modern Data & AI platform that supports the next generation of issuer processing infrastructure. This role is vital for designing real-time and batch data pipelines used in fraud detection, reconciliation, and regulatory reporting. If you're an expert in streaming technologies, cloud data architecture, and high-volume transaction processing, this is your opportunity to work on cutting-edge systems at global scale.

What you get to do::

Issuer Processing Data Engineering

• Design and build pipelines for end-to-end card transaction event processing (authorization through settlement).
• Normalize and process ISO8583/JSON payloads, including de-duplication and correlation of retries, reversals, and late-clearing messages.
• Develop frameworks for scheme fee computation, network clearing reconciliation, and settlement reporting.
• Build client-level reporting capabilities for operational and audit purposes.
• Collaborate with Risk, Fraud, and Compliance teams to integrate real-time analytics and scoring mechanisms.

Data Architecture & Platform Engineering

• Design and implement both streaming and batch data pipelines using Kafka, Flink, Spark, and Dataflow.
• Manage schema evolution and contract validation for changing transaction formats.
• Build and maintain data lakehouse environments (e.g., Delta Lake, Iceberg).
• Enable performant OLAP workloads using BigQuery, Redshift, or Snowflake through appropriate data modeling strategies.
• Develop ETL/ELT orchestration with tools like Airflow, Dagster, or dbt.
• Implement observability, lineage tracking, and data quality monitoring using tools like Great Expectations and Monte Carlo.

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:

• Advanced expertise in streaming data technologies (Kafka, Flink, Spark).
• Strong programming skills in Python, Scala, or Java.
• In-depth experience with ISO8583, issuer/acquirer transaction processing, and financial-grade systems.
• Deep understanding of OLTP offload strategies and ledger-consistent data modeling.
• Skilled in building scalable data infrastructure in cloud environments (GCP, AWS).
• Familiarity with financial compliance standards (e.g., PCI-DSS, data masking, encryption).
• Strong communication and collaboration skills across technical and business stakeholders.
• Analytical mindset and ability to handle complex data scenarios involving reconciliation, discrepancies, and reporting.

Education & Experience:

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.
• 7–12 years of experience in data engineering with demonstrated contributions to large-scale, real-time data systems.
• Ideal candidates will have a strong grasp of MLOps practices and experience working with machine learning data pipelines, particularly those used in areas like fraud or anomaly detection.
• Familiarity with Change Data Capture (CDC) tools such as Debezium or Kafka Connect is also valued.
• Experience working within regulated financial institutions or directly with card network integrations is highly regarded.
• Hands-on experience in ledger verification, reconciliation logic, and automated financial reporting.
• Contributions to open-source projects in the big data or fintech domains demonstrate a strong commitment to technical excellence and community engagement.