Senior Data Engineer – Snowflake, dbt, AWS

• Build and run batch and streaming ingestion pipelines from databases, event streams and third-party APIs
• Own storage architecture across lake, lakehouse and warehouse, focusing on partitioning, cost and query performance
• Keep pipelines observable and restartable through orchestration, automated testing, alerting and clean recovery
• Apply software engineering practices to data, including infrastructure as code, CI/CD, code reviews and version control
• Define data contracts with producing teams to control schema drift
• Manage access, retention and lineage
• Write documentation that outlasts the engagement
• Work directly with senior leadership and client teams on production data systems
• Build and run pipelines and platforms moving data from source systems to the warehouse for a leading retail client

• 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
• Experience with a second cloud provider (GCP or Azure) preferred
• Spark/PySpark at scale and Databricks preferred
• Streaming and pub/sub brokers: Kafka, Kinesis, Pub/Sub or MQTT preferred
• Open table and file formats: Parquet, Apache Iceberg, Delta Lake preferred
• Docker, Kubernetes and GitHub Actions preferred
• Data quality frameworks in production: Great Expectations, Soda or Monte Carlo preferred
• AI data infrastructure: embedding pipelines, vector stores, feature stores preferred
• NoSQL stores (e.g. MongoDB) and marketing data sources (Google Ads, Meta, CRM APIs) preferred
• A cost engineering mindset: making pipelines cheaper and quantifying the savings preferred
• Experience in regulated environments (GDPR, access control, auditable lineage) preferred

• 15th month salary
• Health insurance covering your family
• Birthday off
• Mobility program for digital nomads
• Real work-life balance