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About the Role

We're looking for a passionate Data Engineer to join our innovative team in London or Newcastle and help shape the future of our Data Lakehouse platform! In this role, you'll collaborate closely with business and technology teams across Wealth Management Europe (WME), building and optimising the data pipelines that turn raw financial data into trusted, actionable insights using cutting-edge tools like Databricks, Azure Data Factory, and Delta Lake.

Responsibilities

• Design, build, and maintain scalable pipelines across our Bronze, Silver, and Gold medallion architecture.
• Perform daily monitoring of pipeline health and proactively resolve issues end-to-end.
• Leverage Azure, Databricks, and Data Factory to automate repetitive tasks, enhance performance, and future-proof our platform.
• Champion DevOps & DataOps practices including Gitflow branching, structured pull request reviews, and rigorous testing.
• Partner with data analysts, architects, and business stakeholders to translate requirements into technical solutions.
• Identify opportunities to improve pipeline performance, platform architecture, and engineering processes.

Requirements

• Proven experience in Data Engineering working within a Lakehouse environment (Databricks is preferable).
• Strong SQL/T-SQL skills and a knack for database design and modelling.
• Experience and knowledge of Python and PySpark.
• Proven experience building and optimising big data pipelines at scale with structured and semi-structured data.
• Hands-on experience with Azure Data Factory, ADLS Gen2, and Azure SQL Database.
• Solid Azure DevOps practices including Git, branching strategies, and agile delivery.
• A thorough approach to testing - source system through to the presentation layer.
• Familiarity with Infrastructure-as-Code (e.g. Terraform).
• Experience with data governance, quality, and security processes.
• Familiarity with Azure DevOps Pipelines and CI/CD for data platform deployments.
• A curious, problem-solving attitude and a passion for automating manual processes.

Skills

• Big Data Management
• Cloud Computing
• Database Development
• Data Mining
• Data Warehousing (DW)
• ETL Processing
• Group Problem Solving
• Quality Management
• Requirements Analysis
• Databricks
• Azure Data Factory
• Delta Lake
• Python
• PySpark
• Azure
• ADLS Gen2
• Azure SQL Database
• Azure DevOps
• Git
• Terraform

Location

• London
• Newcastle

Work Type

• Permanent
• Full-time
• Hybrid

Benefits

• Opportunities to work with the best in the field.
• Ability to make a difference and lasting impact.
• Work in a dynamic, collaborative, progressive, and high-performing team.

About the Company

• RBC is a global financial institution with a purpose-driven, principles-led approach to delivering leading performance.
• Our success comes from the 84,000+ employees who bring our vision, values and strategy to life so we can help our clients thrive and communities prosper.
• As Canada’s biggest bank, and one of the largest in the world based on market capitalization, we have a diversified business model with a focus on innovation and providing exceptional experiences to more than 16 million clients in Canada, the U.S. and 34 other countries.
• We are proud to support a broad range of community initiatives through donations, community investments and employee volunteer activities.

Equal Opportunity

• At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC.
• We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world.
• Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities.
• RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.