Our client is a globally regulated financial services group operating across multiple jurisdictions, offering advanced trading and financial technology solutions across FX, CFDs, digital assets, and related products. The organization is undergoing a strong data and technology transformation, investing heavily in scalable data infrastructure to support analytics, reporting, risk management, and business intelligence across the group.
Role OverviewThe Data Engineer will be responsible for designing, building, and maintaining scalable data pipelines and data platforms that support analytics, reporting, and decision-making across the business. The role requires close collaboration with engineering, product, finance, risk, and compliance teams to ensure data accuracy, availability, and reliability within a regulated financial environment.
This is a hands-on technical role suited for someone comfortable working with complex data sources, high volumes, and strict data governance requirements.
Key Responsibilities- Design, build, and maintain scalable ETL/ELT data pipelines from multiple internal and external data sources, including trading platforms, CRM, finance, and operational systems
- Develop and manage data warehouses, data lakes, and optimized data models for analytics and reporting use cases
- Ensure data quality, consistency, validation, and integrity across all data pipelines and storage layers
- Implement monitoring, logging, and alerting to proactively identify and resolve data issues
- Optimize data performance, query efficiency, and pipeline reliability
- Work closely with BI, analytics, and data science teams to enable reporting, dashboards, and advanced analytics use cases
- Collaborate with engineering and product teams on data architecture and integration design
- Support data governance, security, and compliance requirements in line with regulatory standards
- Document data pipelines, models, and technical processes to ensure maintainability and knowledge sharing
- Proven experience as a Data Engineer, preferably within financial services, fintech, trading, or regulated environments
- Strong proficiency in SQL and Python for data processing and pipeline development
- Hands-on experience with data warehousing concepts, dimensional modeling, and large-scale datasets
- Experience building and maintaining ETL/ELT pipelines and working with modern data stacks
- Familiarity with cloud-based data platforms and infrastructure
- Strong understanding of data quality, validation, and governance best practices
- Ability to work cross-functionally with technical and non-technical stakeholders
- Strong attention to detail and ability to operate in fast-paced, high-accuracy environments
- Excellent problem-solving and documentation skills
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