Senior Data Engineer
Salary not stated · Compare with UK Data Engineer pay →
Job Purpose
At Intercontinental Exchange (ICE), we engineer technology, exchanges and clearing houses that connect companies around the world to global capital and derivative markets. With a leading-edge approach to developing technology platforms, we have built market infrastructure in all major trading centers, offering customers the ability to manage risk and make informed decisions globally. By leveraging our core strengths in technology, we continue to identify new ways to serve our customers and transform global markets.
ICE is seeking a Senior Data Engineer who will be responsible for design and optimise SQL queries, develop stored procedures, and participate in the migration and modernisation of legacy applications to support ICE Derivatives and ICE Mortgage. The candidate should have a strong background in SQL and scripting.
Responsibilities
- Provides Snowflake-based data warehouse design and development for projects involving new data integration, migration, and enhancement of existing pipelines.
- Designs and develops data transformation logic using SQL, Snowflake stored procedures, and Python-based scripts for ETL/ELT workloads.
- Builds and maintains robust data pipelines to support reporting, analytics, and application data needs.
- Creates and maintains Snowflake objects like tables, views, streams, tasks, file formats, and external stages.
- Participates in project meetings with data engineers, analysts, business users, and product owners to understand and implement technical requirements.
- Writes technical design documentation based on business requirements and data architecture principles.
- Develops and/or reviews unit testing protocols for SQL scripts, procedures, and data pipelines using automation frameworks.
- Completes documentation and procedures for pipeline deployment, operational handover, and monitoring.
- May mentor or guide junior developers and data engineers.
- Enable real-time and batch data processing architectures that support AI-driven analytics, recommendations, forecasting, and intelligent automation.
- Optimise cloud data platforms for AI scalability, including data lakehouse architectures, semantic layers, and high-performance data retrieval patterns.
- Stays current with Snowflake features, best practices, and industry trends in cloud data platforms.
- Performs additional related duties as assigned.
Knowledge and Experience
- 5+ years of professional experience in data engineering or database development.
- Strong Hands-on experience:
- Writing complex SQL queries and stored procedures
- Database stored procedures, functions, views, and schema design
- Using Streams, Tasks, Time Travel, and Cloning
- Proficiency in database performance tuning and performance optimisation — clustering, warehouse sizing, caching, etc.
- Experience configuring external stages to integrate with cloud storage (AWS S3, Azure Blob, etc.).
- Experience writing Python/Shell scripts for data processing.
- Expert knowledge of Snowflake (Tidal is an added advantage).
- Proficiency in using Git and working within Agile/Scrum SDLC environments.
- Familiarity working in a Software Development Life Cycle (SDLC) leveraging Agile principles.
- Excellent analytical, decision-making, and problem-solving skills.
- Ability to multitask in a fast-paced environment with a focus on timeliness, documentation, and communication with peers and business users.
- Strong verbal and written communication skills to engage both technical and non-technical audiences at various organisational levels.
- Bachelor’s degree in computer science, Engineering, or related field (or equivalent experience).
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