Senior Data Engineer - Financial Analytics

Job Terms:

• 12-month contract (extendable)
• Open to European candidates who are willing to relocate
• Full relocation assistance offered

Key Responsibilities

• Lead the architecture and development of data pipelines and data platforms to support high-performance financial analytics.
• Design and manage end-to-end ETL workflows, ensuring efficiency, scalability, and data integrity.
• Collaborate with cross-functional stakeholders to define data requirements and governance standards.
• Optimize data systems for performance, cost, and reliability across cloud ecosystems (AWS, Azure).
• Implement real-time data processing and integration using Spark, PySpark, and other big data tools.
• Oversee data migration projects to Snowflake, Redshift, or equivalent platforms.
• Provide technical mentorship to junior engineers and establish best practices in data engineering and DevOps workflows.
• Integrate financial data sources, ensuring compliance with data privacy and security regulations.
• Drive automation initiatives to reduce manual intervention and improve data refresh cycles.
• Apply AI and machine learning techniques to enhance data-driven insights and automation.

Required Qualifications

• Minimum of 7+ years of experience in data engineering, with a focus on financial data pipelines.
• Proven expertise in AWS (Glue, Lambda, S3, Redshift) and/or Azure (Data Factory, Databricks, Data Lake) environments.
• Strong command of Python, PySpark, SQL, and data modeling principles.
• Experience in AI and machine learning applications within data engineering contexts.
• Skilled in ETL pipeline orchestration, API integration, and data warehouse design.
• Hands-on experience with Power BI, Tableau, or equivalent BI platforms.
• Background in managing distributed data systems using Hadoop, Delta Tables, or similar frameworks.