Software Engineer - Cloud Data Pipelines (R/Python)
Infinity Quest
UK
6 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
£35,920.0
Working hours
Regular working hours
Job source
Tech stack
Airflow
Automation of Tests
Microsoft Azure
BigQuery
Cloud Computing
Cloud Database
Cloud Engineering
Computer Programming
Continuous Integration
Data Integrity
Data Stores
Data Flow Control
+30 more
Github
Python (Programming Language)
PostgreSQL
SQL Azure
Software Engineering
SQL Databases
Workflow Management Systems
Data Logging
Data Processing
Scripting
Google Cloud
Azure Data Factory
Snowflake
Git
Containerization
Gitlab-ci
Kubernetes
Code Testing
Google Cloud Functions
Bicep
Non-relational Database
Cloud Integration
Api Design
Terraform
Azure Synapse Analytics
Software Version Control
Data Pipelines
Serverless Computing
Docker
Databricks
Job description
We are seeking a Software Engineer to design, build, and maintain robust data pipelines that ingest, process, and execute custom R and Python scripts at scale. You will work within our cloud infrastructure (Google Cloud Platform or Azure) to automate data workflows, ensure high performance, and integrate advanced analytical models into production environments., * Execute R/Python Workloads: Containerize, deploy, and orchestrate custom R and Python scripts to run reliably in cloud-native serverless or containerized environments.
- Cloud Integration: Leverage managed cloud services on GCP (e.g., Cloud Functions, Cloud Run, BigQuery, Dataflow) or Azure (e.g., Azure Data Factory, Azure Functions, Databricks, Synapse Analytics).
- Workflow Orchestration: Implement and maintain workflow tools (such as Apache Airflow or Prefect) to schedule and monitor script execution.
- Ensure Data Quality: Implement automated logging, error handling, and testing frameworks to validate data integrity and script outputs.
- Optimize Performance: Tune data processing jobs and cloud resource allocation for cost-efficiency, speed, and scalability.
Requirements
- Programming: Advanced proficiency in Python and/or R, with strong experience writing clean, modular, and well-tested code.
- Cloud Platforms: Hands-on production experience with either Google Cloud Platform (GCP) or Microsoft Azure.
- Containerization & Tools: Experience with Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, GitLab CI).
- Data Stores: Proficiency with SQL and relational/non-relational databases (PostgreSQL, BigQuery, Snowflake, or Azure SQL).
- Software Engineering Practices: Solid foundation in version control (Git), automated testing, and API design., * Experience migrating legacy local R/Python analytical scripts into distributed cloud architectures.
- Knowledge of Infrastructure as Code (Terraform or Bicep).
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