Senior Data Engineer – Contractor

myPOS

Senior Data Engineer building scalable pipelines and MLOps automation for myPOS, a fintech payments company. Enabling trusted analytics data and reliable payment-business decision-making.

Posted 8/10/2026contractRemote • 🇬🇷 GreeceSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and maintaining scalable data pipelines and infrastructure, with strong proficiency in Python and SQL. Familiarity with cloud environments and orchestration tools is essential for optimizing data workflows and ensuring data quality.

Highest-signal resume keywords

Data Pipeline DevelopmentPython ProgrammingSQL ProficiencyCloud Environment ExperienceData Quality Best Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringData ArchitectureETL/ELT PatternsIncremental Data IngestionData ModelingPerformance OptimizationData StructuresMLOps AutomationDebugging SkillsData Governance

Soft Skills

Clear Communication

Tools & Technologies

AirflowDagsterDatabricks WorkflowsTerraformCI/CD Practices

Industry Keywords

Cloud ProviderData WarehousingDimensional ConceptsDataOps PracticesAuditability

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 jobs, queries, and partitioning
Ensure secure and compliant data handling, 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 for ML CI/CD, environments, artifacts, and versioning of data, models, and code

Requirements

What you’ll need

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
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, Terraform/IaC, and/or DataOps practices
Ability to debug issues across data, infrastructure, pipelines, and deployments
Clear communication across engineering, analytics, and business stakeholders
English CV required

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