Data Engineer
at CapitalCom
London, England, United Kingdom -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 09 Feb, 2025 | Not Specified | 10 Nov, 2024 | 2 year(s) or above | Spark,Data Engineering,Docker,Python,Cloud Services,Airflow,Kubernetes,Postgresql | No | No |
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Description:
We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talent team.
As a Data Engineer, you will be responsible for designing, implementing, and optimizing batch and streaming data pipelines that ensure efficient and reliable data flow throughout the company. You will support our existing data infrastructure while also extending the toolset with new technologies. You’ll collaborate closely with different teams to propose improvements and innovations that enhance data accessibility and performance.
REQUIREMENTS:
- 2+ years of experience in data engineering, focusing on building and maintaining data pipelines.
- Strong expertise in Python and working with data orchestration tools like Airflow.
- Experience with SQL databases such as PostgreSQL and Redshift.
- Familiarity with AWS cloud services and container orchestration tools like Docker and Kubernetes.
- Experience with Spark is a plus.
- Ability to collaborate with various teams and propose innovative solutions.
Responsibilities:
- Data Pipeline Development: Build, implement, and maintain batch and streaming data pipelines that support the company’s data requirements.
- Toolset Extension: Continuously expand the data engineering toolkit by integrating new technologies and methodologies that improve performance and scalability.
- Stack Support: Provide support and maintenance for the current data infrastructure, ensuring that all systems remain operational and efficient.
- Continuous Improvement: Propose and implement new technologies and improvements to optimize the data engineering process.
- Collaboration: Work with cross-functional teams to gather requirements and translate them into technical specifications for the data pipeline.
REQUIREMENT SUMMARY
Min:2.0Max:7.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
London, United Kingdom