AWS Cloud Data Platform Engineer
Summary: The AWS Cloud Data Platform Engineer role involves designing and developing scalable data pipelines using AWS services and tools such as Snowflake, Airflow, and Databricks. The position requires proficiency in Python and experience with various data processing technologies. The role is based in Glasgow and requires 2-3 days on-site work. The contract is set to last until December 31, 2026, with a competitive daily rate offered.
Key Responsibilities:
- Design and develop scalable data pipelines using AWS services.
- Implement data ingestion from multiple sources including APIs and databases.
- Build and maintain data models using dbt and write complex SQL transformations.
- Manage data documentation and lineage within DBT.
- Create and deploy Airflow DAGs on Kubernetes.
- Optimize data workflows for batch and real-time processing using Databricks and Apache Spark.
- Utilize Terraform for infrastructure as code and manage Snowflake integrations.
- Implement data testing and validation processes.
Key Skills:
- AWS services (CloudFormation, IAM, S3, Glue, Lambda, EKS, ECS, VPC).
- Terraform knowledge (modules, providers, Snowflake provider).
- Experience with Snowflake and its features (Snow sight, data marketplace, Snowpipe).
- Proficiency in Python and PySpark.
- Familiarity with Airflow and Kubernetes.
- Experience with Databricks and Apache Spark.
- Strong SQL skills for data transformations.
- DevOps tools (GitLab, Jenkins, SonarQube).
Salary (Rate): £375 per day
City: Glasgow
Country: United Kingdom
Working Arrangements: on-site
IR35 Status: inside IR35
Seniority Level: Mid-Level
Industry: IT
We are a Global Recruitment specialist that provides support to the clients across EMEA, APAC, US and Canada. We have an excellent job opportunity for you.
Role Title: AWS Cloud Data Platform Engineer
Location: Glasgow
Duration: 31/12/2026
Days on site: 2-3
Rate: £375 per day all inc. (PAYE through Umbrella)
Role Description:
Must have Skills:
AWS: Cloud formation, Service Catalog, IAM, S3, Glue, Lambda, Knowledge python SDK, boto, EKS, ECS, ECS, VPC, SUBNETS, NACLs.
Terraform: Modules, providers, terraform enterprise, Snowflake terraform provider knowledge.
Snowflake: Snow sight, Python SDK for snowflake, Stage, storage integration, Data marketplace, direct shares, listings, catalog linked database, Apache Iceberg, external tables, Catalog integrations, Snowpipe, external volume, Cortex ai,privatelink.
Airflow: Dag creation, operators, connections, deployment on Kubernetes, Astronomer.
DBT:
Build and maintain data models using dbt
Write complex SQL transformations to clean and structure data
Develop modular, reusable data pipelines
Implement data testing and validation (eg, schema tests, data quality checks)
Manage data documentation and lineage within DBT
SPARK: Distributed computing fundamentals, PYSPARK, GLUE JOB USING PYSPARK.
Devops: Gitlab, Jenkins, Kubernetes, SonarQube.
Databricks:
Design and develop scalable data pipelines using Databricks and Apache Spark
Build and optimize data workflows for batch and Real Time processing
Transform and process large datasets using PySpark, SQL, and Delta Lake
Implement data ingestion from multiple sources (APIs, streaming, databases)
PYTHON PROFIENCY NEEDED
If you are interested in this position and would like to learn more, please send through your CV and we will get in touch with you as soon as possible. Please note, candidates are often Shortlisted within 48 hours.
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