DataOps Engineer (Python/AWS)

Location: Madrid, Spain (Hybrid)

Company

hirify.global develops a cloud-based platform for personalization, recommendations, analytics, and client performance reporting.

What you will do

• Design, build, and maintain reliable data ingestion, processing, orchestration, and transformation pipelines.
• Develop and maintain Python-based backend services and integrations for the Personalization platform.
• Operate AWS-based services and data workloads, contributing to Infrastructure as Code, CI/CD, and safe deployments.
• Improve observability through logging, metrics, tracing, alerting, and OpenTelemetry-based practices.
• Investigate data quality, integration, platform, and customer-environment issues during onboarding and ongoing operations.
• Review code and designs, support less experienced engineers, and improve architecture, tooling, reliability, and engineering practices.

Requirements

• Strong Python development skills with experience building production backend or data systems.
• Strong SQL skills and experience with analytical or operational datasets.
• Experience designing, building, or maintaining data pipelines, workflow orchestration, data modelling, transformation, and data quality processes.
• Hands-on experience operating cloud systems, preferably AWS, including production observability with logging, metrics, tracing, and monitoring.
• Experience with automated unit and integration testing, CI/CD, debugging, code review, refactoring, and maintenance of production systems.
• Several years of experience delivering production software and data systems.

Nice to have

• AWS serverless technologies such as Lambda, API Gateway, SQS, S3, Athena, or Glue.
• Infrastructure as Code with CloudFormation, Terraform, or AWS CDK.
• OpenTelemetry, columnar data formats, analytical data platforms, Elasticsearch, or similar technologies.
• React and TypeScript, data science and machine learning, recommendation systems, personalization, or analytics products.
• Agile development, AWS certifications, or TV, VOD, streaming, and media domain knowledge.

Culture & Benefits

• Collaborative engineering environment with cross-functional work across data, backend, platform, frontend, and data science areas.
• Participation in the full software development lifecycle from technical design through deployment, monitoring, and continuous improvement.
• Opportunities to contribute to client integrations and platform capabilities used for personalization, recommendations, and analytics.