Data Engineer

We’re looking for a Data Engineer to own the design, implementation, and operation of production-ready data systems. You’ll independently deliver end-to-end pipelines, from ingestion through transformation and serving, making the technical decisions that keep our systems reliable, scalable, and maintainable across the full data lifecycle.

What you will be doing

• Design and implement end-to-end production data pipelines covering ingestion, transformation, orchestration, and serving layers.
• Build and operate distributed and non-distributed processing systems, choosing the right approach based on workload, data volume, latency, and cost.
• Design transformation layers with tools such as dbt, ensuring dependency management and CI/CD integration.
• Select the right storage technologies (relational and non-relational) for each system and workload.
• Design and maintain orchestrated workflows with frameworks such as Airflow or Prefect.
• Implement batching and incremental processing strategies to handle growing datasets efficiently.
• Build systems that behave reliably under retries, failures, and increasing scale.
• Ensure systems are observable and diagnosable through logging, monitoring, and validation.
• Work closely with DevOps to deploy and operate systems in production environments.
• Design and operate pipelines supporting AI and agentic workloads, considering freshness, semantic consistency, and point-in-time correctness.
• Take ownership of reliability and maintainability well beyond initial delivery.
• Participate actively in code reviews, identifying performance and reliability improvements.
• Support and mentor junior engineers in engineering practices and technical implementation.

What we’re looking for

• 3+ years of experience in data engineering (a reference point: at JTA, competence matters more than years).
• Ability to independently deliver end-to-end pipelines across ingestion, transformation, orchestration, and serving.
• Strong Python skills for production-grade data processing: clean, tested, maintainable code.
• Strong T-SQL for building, exploring, validating, and troubleshooting datasets.
• Hands-on experience with dbt, including dependency management and CI/CD integration.
• Experience with code-first orchestration frameworks (Airflow, Prefect).
• Experience with distributed processing (e.g. PySpark), and sound judgment on when distributed vs. non-distributed processing is appropriate.
• Comfortable with both relational and non-relational databases, able to choose the right one per workload.
• Experience with containerized environments (Docker) and collaborating with DevOps on deployment and operations.
• Solid engineering practices: testing, logging, observability, code review, and version control (Git).
• Ability to investigate and resolve failures, inconsistencies, and reliability issues independently.
• Understanding of data governance, cataloging, and lineage principles.
• Ownership mindset: you handle ambiguity with autonomy and stay accountable for your systems beyond delivery.
• Team-oriented, proactive communicator who provides guidance and feedback to more junior engineers.
• Fluent in English, both written and spoken.
• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a related field (or equivalent experience).

Perks

• Annual gross salary between €30,000 and €45,000, depending on experience and qualifications, with room for flexibility
• Fully remote or hybrid work (you decide)
• Meal allowance: €10.46 per day (via card)
• 15th month bonus salary policy
• 4 extra vacation days
• Participation in international projects
• Health insurance (for you, your spouse and children)
• Life insurance
• Company-paid certifications
• Team building activities
• Innovative and young culture

Location

We’re based in Porto, Portugal. Remote work is possible, but we are only considering candidates located in Portugal.