Senior Data Engineer

About the role

We are looking for a hands‑on Senior Data Platform Engineer to own, scale, and modernize our data platform, ensuring it is scalable, reliable, secure, cost‑efficient and supports both operational and analytical workloads.

Key responsibilities

• Own deployment, scaling and orchestration of the core data stack using AWS Managed Workflows for Apache Airflow (MWAA) and design the overall platform architecture.
• Configure and optimise raw data storage in S3, manage Redshift external schemas (Spectrum) and the AWS Glue Data Catalog, define partitioning strategies and use columnar formats such as Parquet.
• Design scalable analytical data models using dimensional modelling and lake‑house best practices.
• Manage and optimise dbt projects to transform, test and materialise data in Amazon Redshift.
• Build observability through monitoring, logging, alerting and operational dashboards.
• Perform performance and cost optimisation for Redshift, S3 layouts and workloads.
• Implement CI/CD pipelines for dbt, Airflow DAGs and infrastructure using IaC.
• Support BI tools such as Metabase ensuring high performance and access control.
• Collaborate on security, documentation and stakeholder requirements.

Required profile

• Extensive hands‑on experience with AWS data services, especially MWAA, Redshift/Spectrum, S3, IAM and Glue.
• Advanced proficiency with dbt, including project structuring, custom macros and incremental models.
• Strong Python programming skills for Airflow DAG development and automation.
• Expert‑level SQL knowledge with deep understanding of Redshift distribution and sort keys.
• Solid experience deploying infrastructure as code using Terraform or AWS CloudFormation.

Required skills

• AWS (MWAA, Redshift, Redshift Spectrum, S3, IAM, Glue)
• dbt
• Python
• SQL (Redshift)
• Terraform or AWS CloudFormation
• Airflow