Data Engineer

We are looking for a skilled Data Engineer with hands-on experience in designing, building, and supporting scalable data pipelines and data products across modern cloud data platforms., Data Engineering & Pipeline Development

• Design, build, and maintain scalable data pipelines using Azure Data Factory.
• Develop robust ETL/ELT processes to ingest, transform, and publish data across enterprise platforms.
• Work with structured and semi-structured data, applying appropriate data modelling, validation, and quality checks.
• Write and optimise SQL for data transformation, reconciliation, and performance tuning.

Cloud Data Platform & DataOps

• Develop and support data solutions on Snowflake as a core cloud data platform.
• Use DataOps.live practices and tooling to support version-controlled, automated, and repeatable data deployments.
• Collaborate with engineering and platform teams to implement CI/CD, environment management, and release controls for data assets.
• Support monitoring, troubleshooting, and continuous improvement of data pipelines and platform processes.

Data Product Development

• Contribute to the design and delivery of reusable Data Products aligned to business and analytical needs.
• Apply data product principles such as ownership, discoverability, quality, reusability, and clear documentation.
• Work with business stakeholders, analysts, and technical teams to understand data requirements and translate them into reliable data solutions.
• Ensure data outputs are trusted, governed, and suitable for downstream reporting, analytics, and operational use cases.

Good-to-Have: Reporting & Analytics

• Familiarity with Power BI reporting, semantic models, datasets, and dashboard development.
• Ability to support reporting teams by providing well-structured, performance-optimised data models.
• Understanding of business KPIs and how data engineering outputs support analytics and decision-making.

The ideal candidate should have strong experience with Azure Data Factory, Snowflake, and DataOps. live, along with a good understanding of Data Product concepts, data integration, orchestration, and engineering best practices. Power BI experience is desirable and would be considered a good-to-have skill., * Hands-on experience with Azure Data Factory, including pipeline orchestration, triggers, linked services, datasets, and monitoring.

• Strong SQL skills and experience working with cloud data platforms such as Snowflake.
• Experience with DataOps.live or similar DataOps/DevOps tooling for automated deployment and environment management.
• Understanding of Data Product concepts, metadata, governance, and documentation practices.
• Good-to-have experience in Power BI for reporting, dashboards, and data visualisation.
• Knowledge of Python or another scripting language would be advantageous.

Key Competencies

• Strong analytical and problem-solving skills.
• Ability to build reliable, scalable, and maintainable data solutions.
• Good communication skills with the ability to work across business, data, and engineering teams.
• Attention to detail, especially around data quality, reconciliation, and documentation.
• Ability to work in an agile delivery environment and manage priorities effectively.