Data Engineer

ABOUT THE OPPORTUNITY

We are looking for a Senior Data Engineer to join a technology sector project focused on developing reliable, scalable and production-ready data platforms.

You will contribute to the reliability, security and performance of data solutions supporting business-critical operations.

The role requires strong engineering expertise, autonomous problem-solving and effective collaboration with distributed teams. Professional working proficiency in English is mandatory.

National and international travel may be required, with an estimated frequency of up to 15%, depending on project needs.

WHAT YOU WILL DO

- Design, develop and maintain scalable batch and streaming data pipelines across multiple data sources.

- Build and optimize data ingestion, processing and transformation workflows for cloud-based data platforms.

- Develop and maintain data warehouse solutions, ensuring consistent data modeling and transformation practices.

- Implement automated workflows for data orchestration, deployment and infrastructure management.

- Establish automated testing, monitoring and alerting mechanisms to improve data pipeline reliability.

- Diagnose production issues, implement corrective actions and improve recovery procedures.

- Collaborate with engineering teams to define data contracts, manage schema changes and maintain data lineage.

- Apply data access controls and information security practices throughout the data lifecycle.

- Use AI-assisted development tools responsibly, validating generated code for accuracy, maintainability and security.

- Contribute to technical improvements, knowledge sharing and the continuous optimization of data engineering practices.

WHAT WE ARE LOOKING FOR

- Senior-level professional experience in data engineering, including the development and maintenance of production data systems.

- Strong practical experience with Python and SQL in complex data processing environments.

- Proven ability to design and maintain reliable data pipelines and cloud-based data architectures.

- Experience working with large-scale data processing, streaming technologies and analytical data platforms.

- Ability to work autonomously, assess technical risks and take responsibility for delivery quality.

- Strong analytical thinking, troubleshooting capabilities and a structured approach to problem-solving.

- Collaborative mindset, clear technical communication and willingness to share knowledge.

- Experience using AI development tools with appropriate human oversight and code validation.

- Professional working proficiency in English, both written and spoken, for technical and business communication.

- Availability for occasional national and international travel, estimated at up to 15%.

TECHNICAL SKILLS

- Python and SQL for production data engineering.

- AWS cloud services and cloud-based data infrastructure.

- Batch processing, real-time data streaming and API integration.

- Apache Airflow, Dagster, Azure Data Factory or equivalent orchestration platforms.

- Snowflake and dbt for data warehousing and transformation.

- Dimensional Modeling and Data Vault methodologies.

- Apache Spark, PySpark, Databricks, Apache Kafka, Amazon Kinesis or Google Pub/Sub.

- CI/CD pipelines and Infrastructure as Code practices.

- Git, GitHub Actions, Terraform and Docker.

- Automated data testing, observability, monitoring and incident troubleshooting.

- Data contracts, schema evolution, data lineage and access management.

- AI-assisted software development and code quality validation.

NICE TO HAVE

- Experience with Google Cloud Platform or Microsoft Azure.

- Knowledge of GDPR principles and data protection requirements.

- Experience with NoSQL databases, particularly MongoDB.

- Familiarity with marketing platforms, CRM systems and associated APIs.

WHAT WE OFFER

- Fully remote working model.

- Private health insurance from your first day, with no waiting periods and optional family extension.

- Free and confidential psychological support through our TEAM 24 partnership, including specialized resources and live sessions.

- Continuous professional development through training and certification opportunities.

- Opportunities to strengthen expertise in information security, AI governance, quality management and cybersecurity best practices.

- Childcare vouchers and support measures that promote work-life balance.

- A collaborative environment supported by knowledge sharing, professional development and accessible leadership.

- Team initiatives and community activities that strengthen connections across the organization.