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myPOS

Senior Data Engineer – Contractor

myPOS

Senior Data Engineer building scalable pipelines and MLOps infrastructure for myPOS, a fintech payments company. Delivering trusted analytics data and secure cloud data platforms.

Posted 8/10/2026contractRemote • 🇷🇸 SerbiaSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in designing and operating scalable data pipelines and infrastructure, with strong proficiency in Python and SQL. Capable of implementing data quality practices and optimizing workflows for performance and cost in cloud environments.

Highest-signal resume keywords
Data Pipeline DevelopmentPython ProgrammingSQL ProficiencyCloud Environment ExperienceData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data EngineeringData ArchitectureETL/ELT PatternsData ModelingIncremental Data IngestionData Quality Best PracticesPerformance OptimizationData StructuresMLOps AutomationDebugging Data Issues
Soft Skills
Collaborative MindsetClear Communication
Tools & Technologies
AirflowDagsterDatabricks WorkflowsGCPAWSAzureTerraformCI/CDDataOpsObservability Tools
Industry Keywords
Data GovernanceData QualityData InfrastructureData PipelinesCloud ComputingData WarehousingDimensional ConceptsAuditabilityAccess ControlsVersioning

Tech Stack

Tools & technologies
AirflowAWSAzureCloudETLGoogle Cloud PlatformPythonSparkSQLTerraform

About the role

Key responsibilities & impact
  • Design, build, and operate scalable, reliable data pipelines and data infrastructure
  • Build and maintain ingestion, transformation, and export pipelines across multiple sources and destinations
  • Develop and evolve scalable data architecture
  • Partner with analysts and data scientists to deliver curated, analysis-ready datasets and enable self-service analytics
  • Implement data quality, testing, monitoring, lineage, and reliability best practices
  • Optimize workflows for performance, cost, and scalability, including Spark tuning, query optimization, and partitioning
  • Ensure secure, compliant handling of data and models, including access controls, auditability, and governance
  • Contribute to documentation, standards, and continuous improvement of the data platform and engineering processes
  • Build and maintain MLOps automation, including CI/CD for ML, environment management, artifact handling, and versioning of data, models, and code

Requirements

What you’ll need
  • Bachelor’s degree in Computer Science, Engineering, or 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
  • Understanding of data structures, performance, and optimization strategies
  • Hands-on experience with orchestration tools such as Airflow, Dagster, or Databricks Workflows
  • Experience with distributed processing in a cloud environment
  • Experience with analytical data modeling, star and snowflake schemas, data warehouses, 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, Infrastructure as Code such as Terraform, and/or DataOps practices
  • Ability to debug issues across data, infrastructure, pipelines, and deployments
  • Collaborative mindset and clear communication across engineering, analytics, and business stakeholders
  • Strong GCP experience and ecosystem knowledge is a nice-to-have
  • Experience with data governance concepts is a nice-to-have
  • Experience building observability for data systems is a nice-to-have
  • Knowledge of model monitoring concepts is a nice-to-have
  • CV must be submitted in English

Benefits

Comp & perks
  • Excellent compensation package
  • myPOS Academy for upskilling and training
  • Unlimited access to courses on LinkedIn Learning
  • Refer a friend bonus
  • Teambuilding, social activities and networks on a multi-national level