Senior Data Engineer - Investment(80k)

Looking for an experienced senior data engineer on behalf of our client, a leading investment company.

Responsibilities

• Design and build scalable ELT processes and data pipelines to convert complex financial data into actionable insights for investor relations, investment teams, portfolio managers, and risk analysts.
• Develop and maintain semantic data models that define clear relationships among financial data entities, such as trade activity, cash flows, and capital movements, ensuring system-wide data integrity and consistency.
• Reconcile and validate calculations across multiple data sources—including spreadsheets, data warehouses, and financial reporting platforms—to ensure the accuracy of investment analytics and risk metrics.
• Establish and implement robust data quality frameworks to detect and address issues, risks, and anomalies across data assets.
• Partner with portfolio managers, analysts, and cross-functional stakeholders to gather data requirements and deliver scalable, business-aligned solutions.
• Monitor data pipelines and processing performance, proactively resolving issues and introducing enhancements to improve system efficiency.
• Automate recurring data operations and reporting tasks to drive operational efficiency and reduce manual workload.
• Ensure adherence to data governance standards, regulatory compliance, and industry best practices in all data-related activities.
• Produce compelling financial reports and presentations that distill complex datasets into clear, impactful investment insights and recommendations.

Requirements

• Expertise in SQL and Python for developing data pipelines and performing advanced data manipulation.
• Hands-on experience with data integration, data modeling, and designing data lake and data warehouse architectures.
• Proficiency in data visualization tools such as Tableau, Power BI, or equivalent platforms for building financial dashboards and analytical reports.
• Strong knowledge of financial data structures, particularly in the domains of private credit markets and fund accounting.
• Exceptional analytical skills with the ability to conduct root cause analysis on data quality issues and operational inefficiencies.
• Experience in implementing and maintaining data validation frameworks and rigorous data testing strategies to ensure accuracy and reliability.