data engineer in fintech

myPOS provides payment solutions that help businesses accept payments and grow. Since 2014, the company has offered multicurrency accounts, e-commerce tools, and accessible payment services for businesses of different sizes.

• 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 data, model, and code versioning.

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience;
• 6+ Years of experience as a Data Engineer building and maintaining production-grade pipelines and datasets;
• Strong Python and SQL skills with knowledge of data structures, performance, and optimization strategies;
• Hands-on experience with orchestration such as Airflow, Dagster, or Databricks Workflows;
• Experience with distributed processing in a cloud environment;
• Experience with analytical data modeling, including star and snowflake schemas, DWH, ETL/ELT patterns, and dimensional concepts;
• Experience building reliable incremental data ingestion pipelines from databases and APIs;
• Familiarity with at least one major cloud provider: GCP, AWS, or Azure;
• Familiarity with CI/CD for data pipelines, IaC with Terraform, and/or DataOps practices;
• Strong troubleshooting mindset and ability to debug issues 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, including BigQuery, Composer, Dataproc, Cloud Run, Dataplex, and Cloud Storage; data governance concepts; observability for data systems; model monitoring concepts.

• Excellent compensation package;
• MyPOS Academy for upskilling and training;
• Unlimited access to LinkedIn Learning courses;
• Refer a friend bonus;
• Teambuilding, social activities, and multinational professional networks;
• Contract position.