Sr Data Engineer
Indexed description
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.
Key Responsibilities
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.
- 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.
- 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.
- 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.
- 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.
- 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.
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