BI Engineer
Indexed description
You will be a self-starter, taking the initiative to understand the whole data lifecycle, Trayport’s products and business to transform complex data into actionable insights.
Key Responsibilities
- Architecture & Engineering: Design, build, and maintain a robust data warehouse. Oversee the ingestion of varied and complex datasets at scale.
- Schema Design: Collaborate closely with Data Engineers and BI Analysts to design, implement, and optimize data warehouse schemas.
- Dashboard & Visualisation Design: Architect, build, and maintain user-friendly dashboards and complex data visualisations that effectively surface critical business metrics and actionable insights for stakeholders.
- Data Quality & Automation: Champion data quality across the organization. Implement data automation pipelines to ensure accuracy, reliability, and timeliness of data.
- Data Governance & Management: Drive improvements in data governance, ensuring best-in-class data management practices are upheld across the business.
- Stakeholder Collaboration: Act as a strategic partner to the business. Communicate complex technical concepts clearly to all levels of the organization, including the C-suite, to promote data-driven decisions.
- Mentorship & Leadership: Mentor other BI Analysts, actively upskilling the team in technical competencies and best practices.
- Expert SQL: Master-level proficiency in writing, optimizing, and troubleshooting complex SQL queries.
- Programming Skills: Strong programming skills in Python (or a similar) for data manipulation and automation.
- Data Warehousing: Deep knowledge of modern database and data warehouse design principles and architectures.
- BI Tooling: Extensive experience with industry-leading BI tools such as Tableau or similar.
- Version Control: Solid experience using source control, such as Git, for managing code and collaborating with technical teams.
- Exceptional Communication: Outstanding verbal and written communication skills, with the proven ability to translate highly technical concepts for both technical and non-technical leadership
- Data Ingestion & ETL/ELT: Experience using ingestion tooling and orchestration platforms to build and manage automated data pipelines.
- Cloud Data Platforms: Hands-on experience with Snowflake (highly desirable) or similar cloud-based data warehouses (e.g., BigQuery, Redshift).
- Additional Programming: Knowledge of C# and experience working within a .NET environment.
- AI Tooling: Experiencing utilising AI-assisted development tools, such as Github Copilot, or integrating AI capabilities into data workflows with a clear understanding of their strengths and limitations.
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