Senior Data Engineer

At myPOS, we’re all about helping businesses grow and get paid. We make payments simple, smart, and accessible for everyone, but we’re more than just payment solutions - myPOS is a partner in growth. From free multicurrency accounts to powerful e-commerce tools, we’re here to support business owners of all sizes and everyone out there who dreams of starting their own business. As we are expanding our team, we’re looking for a Senior Data Engineer (B2B Contractor) to help us make a real difference in the Fintech industry. Ready to join us and shape the future of payments? Let’s make it happen! As a Senior Data Engineer, you’ll design, build, and operate scalable, reliable data pipelines and data infrastructure. Your work will ensure high-quality data is accessible, trusted, and ready for analytics and data science - powering business insights and decision-making across the company.

Responsibilities

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 (e.g., tuning Spark jobs, query optimization, 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, compliant handling of data and models, including access controls, auditability, and governance practices; Build and maintain MLOps automation: CI/CD for ML, environment management, artifact handling, versioning of data/models/code

Requirements

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 a solid understanding of data structures, performance, and optimization strategies; Hands-on experience with orchestration (like Airflow, Dagster, Databricks Workflows) and distributed processing in a cloud environment; Experience with analytical data modeling (star and snowflake schemas), DWH, ETL/ELT patterns, and dimensional concepts; Experience building reliable incremental data ingestion pipelines from DBs and APIs.; Familiarity with at least one major cloud provider (GCP, AWS, Azure) and deploying data solutions in the cloud; Familiarity with CI/CD for data pipelines, IaC (Terraform), and/or DataOps practices; Strong troubleshooting mindset: ability to debug issues across data, infra, 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; Experience with data governance concepts: access control, retention, data classification, auditability, and compliance standards; Experience building observability for data systems (metrics, alerting, data quality checks, incident response); Knowledge of model monitoring concepts: drift, data quality issues, performance degradation, bias checks, and alerting strategies

Benefits

Vibrant international team operating in hi-tech environment; Excellent compensation package; myPOS Academy for upskilling and training; Unlimited access to courses on LinkedIn Learning; Refer a friend bonus as we know that working with friends is fun; Teambuilding, social activities and networks on a multi-national level