data engineer in fintech

myPOS provides payment solutions that help businesses accept payments and grow. Its products include multicurrency accounts, e-commerce tools, and accessible payment services powered by modern technology.

• Build and maintain data pipelines for ingestion, transformation, and export across multiple sources and destinations;
• Develop and evolve scalable data architecture to meet business and performance requirements;
• Partner with analysts and data scientists to deliver curated, analysis-ready datasets and enable self-service analytics;
• Implement best practices for data quality, testing, monitoring, lineage, and reliability;
• Optimize workflows for performance, cost, and scalability, including Spark jobs, queries, and partitioning strategies;
• Ensure secure data handling and compliance with relevant data protection standards and internal policies;
• Contribute to documentation, standards, and continuous improvement of the data platform and engineering processes;
• Ensure secure and compliant handling of data and models, including access controls, auditability, and governance practices;
• Build and maintain MLOps automation, including CI/CD for ML, environment management, artifact handling, and versioning of data, models, and code.

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience;
• 3+ Years of experience as a Data Engineer building and maintaining production-grade pipelines and datasets;
• Python and SQL skills with a solid understanding of data structures, performance, and optimization strategies for ETL/ELT processes;
• Hands-on experience with orchestration tools such as Airflow, Dagster, or Databricks Workflows and distributed processing in a cloud environment;
• Familiarity with at least one major cloud provider: GCP, AWS, or Azure;
• Strong troubleshooting skills across data, infrastructure, pipelines, and deployments;
• Collaborative mindset and clear communication across engineering, analytics, and business stakeholders;
• Nice to have: Strong GCP experience and ecosystem knowledge, BigQuery, Composer, Dataproc, Cloud Run, Dataplex, Cloud Storage, reliable incremental data ingestion from databases and APIs, analytical data modeling, star and snowflake schemas, DWH, ETL/ELT patterns, dimensional concepts, CI/CD for data pipelines, IaC with Terraform, DataOps, data governance, observability for data systems, incident response, and model monitoring.

• Excellent compensation package;
• MyPOS Academy for upskilling and training;
• Unlimited access to LinkedIn Learning courses;
• Refer-a-friend bonus;
• Teambuilding, social activities, and multinational networking;
• Contractor employment.