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Investment Banking – UX and Data Integration Engineer – Snowflake, Databricks, Kafka, Python, SQL, ETL, Power BI, Contract
What will you be doing?
The ENS UX and Data Integration Engineer is responsible for integrating diverse data sources into enterprise analytics platforms and translating business and user requirements into scalable, well designed data solutions.
This role sits at the intersection of data engineering, platform integration, and user experience, ensuring that data powering AI and analytics use cases is structured, performant, and well understood by downstream consumers.
The role requires strong hands on experience with Snowflake and Databricks, as well as the ability to collaborate closely with developers, data owners, and UX stakeholders.
Key Responsibilities:
Partner with developers, data owners, and stakeholders to capture requirements and translate them into clear technical data integration solutions.
Integrate diverse internal and external data sources into Snowflake to support AI model inference and analytical workloads.
Build and support equivalent integrations and pipelines within Databricks for AI and advanced analytics use cases.
Design and implement Snowflake schemas optimized for specific analytical and AI riven use cases.
Design and implement Databricks schemas and data structures aligned to performance, scalability, and usability requirements.
Develop and maintain ETL/ELT pipelines using appropriate tooling and best practices.
Skills that will help you in the role:
Hands-on experience integrating data into Snowflake and Databricks in production environments.
Strong working knowledge of Kafka, Python, and SQL.
Experience building and maintaining data pipelines using modern ETL/ELT tools.
Familiarity with Git-based development workflows.
Experience with visualization or monitoring tools such as Power BI and Grafana.
Solid foundation in Big Data Engineering and Data Analytics principles.
Hybrid working – Glasgow based – Inside IR35
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