Senior Data Engineer (Snowflake/dbt/AWS) - Portugal Full Remote

About this role

Senior Data Engineer (Snowflake/dbt/AWS) - Portugal Full Remote ABOUT THE OPPORTUNITY We’re hiring two Senior Data Engineers to join an international, people-first software engineering company known for high-performance systems used by millions of people worldwide. This is a hands-on role for someone who likes to build, own production systems end to end, and share what they know. You’ll work directly with senior leadership and client teams, in a culture built on empathy, self-organization and the courage to take risks.

AI-assisted engineering is encouraged here, as long as it comes with solid engineering judgment. PROJECT & CONTEXT You’ll join a data project for a leading retail client, building and running the pipelines and platforms that move data from source systems to the warehouse, on production systems where it really matters. Your scope includes: Building and running batch and streaming ingestion pipelines from databases, event streams and third-party APIs Owning storage architecture across lake, lakehouse and warehouse, with a focus on partitioning, cost and query performance Keeping pipelines observable and restartable through orchestration, automated testing, alerting and clean recovery Applying software engineering practices to data: infrastructure as code, CI/CD, code reviews and version control Defining data contracts with producing teams to control schema drift, and managing access, retention and lineage Writing documentation that outlasts the engagement Fully remote from Portugal, with occasional national or international travel (0–15%) depending on project needs.

WHAT WE’RE LOOKING FOR (Required) 5+ years of experience as a Data Engineer, with pipelines built and run in production Advanced, production-grade SQL and Python 3 Extensive experience with ETL/ELT processes and CI/CD for data workloads Hands-on experience with dbt Experience with orchestration tools such as Apache Airflow, Azure Data Factory or Dagster Extensive experience with Snowflake and Terraform Strong understanding of data modelling methodologies: Kimball, Inmon and Data Vault Production experience with AWS Use of AI tooling in daily work, with the review discipline to check what it generates before it ships Fluent English (spoken and written), comfortable working directly with client teams NICE TO HAVE (Preferred) Experience with a second cloud provider (GCP or Azure) Spark/PySpark at scale and Databricks Streaming and pub/sub brokers: Kafka, Kinesis, Pub/Sub or MQTT Open table and file formats: Parquet, Apache Iceberg, Delta Lake Docker, Kubernetes and GitHub Actions Data quality frameworks in production: Great Expectations, Soda or Monte Carlo AI data infrastructure: embedding pipelines, vector stores, feature stores NoSQL stores (e.g.