Data Engineer (Python / SQL / ETL) (2 Year Contract)

Rhino Partners is seeking a Data Engineer to design, develop, and maintain reliable and scalable data pipelines and processing frameworks. You will work closely with technical teams, business stakeholders, and data analysts to support large-scale data integration, transformation, validation, and statistical processing.

The role involves modernising legacy data processes, developing reusable engineering components, and implementing best practices in software development, testing, and deployment to ensure reliable and efficient production workflows.

• Design, develop, and maintain robust ETL pipelines for data ingestion, transformation, validation, and integration from multiple data sources.
• Develop modular, maintainable Python and SQL code to support large-scale data processing and statistical production workflows.
• Modernise and optimise legacy data processes while preserving existing business logic and ensuring accurate reconciliation of outputs.
• Design and maintain database schemas, data models, and storage structures to support efficient data processing and retrieval.
• Develop reusable data engineering components, including common libraries, configuration frameworks, logging utilities, and processing modules.
• Implement and maintain CI/CD pipelines for automated testing and deployment across Development, UAT, and Production environments.
• Configure and manage data pipeline orchestration, scheduling, dependencies, error handling, recovery, and monitoring.
• Apply Git-based version control practices, including branching, merge requests, and code reviews.
• Monitor, troubleshoot, and optimise data pipelines to improve performance, scalability, and operational reliability.
• Collaborate with technical teams and business stakeholders to translate data processing requirements into effective technical solutions.
• Maintain technical documentation and ensure adherence to data governance, security, and engineering standards.

• 4-7 years of professional experience in Data Engineering, Data Platform Development, or related Software Engineering roles.
• Strong proficiency in Python and SQL, with hands-on experience in data transformation, processing, and validation.
• Experience with pandas, Polars, or similar dataframe processing libraries for handling large datasets.
• Hands-on experience in ETL/ELT development, database management, data modelling, and data warehousing.
• Experience with Git/GitLab, including branching strategies, merge requests, code reviews, and CI/CD pipelines.
• Working knowledge of Linux/Unix environments, shell scripting, and command-line tools.
• Understanding of software engineering best practices, including modular programming, configuration management, logging, exception handling, and automated testing.
• Familiarity with data quality management, data governance, access controls, and security practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Good communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Exposure to workflow orchestration tools such as Apache Airflow or other enterprise scheduling platforms.
• Experience with CI/CD automation and deployment processes.
• Experience in legacy system modernisation, data migration, and reconciliation.
• Familiarity with large-scale batch processing and performance optimisation techniques.