Data Analyst, Financial Data Engineering

What you'll do

• Design and maintain scalable ETL/ELT pipelines for financial reporting, risk measurement, and operational decisioning.
• Transform raw data into clean, well-documented datasets to support treasury finance decisions like liquidity management and risk exposure.
• Implement automated data quality standards through testing, monitoring, and alerting systems.
• Establish and manage data freshness SLAs and incident response protocols for production-critical workflows.
• Translate complex business requirements from stakeholders into technical data architecture and strategy.
• Build self-service tools and analytics layers to enable stakeholders to explore trusted data independently.
• Utilize AI tools and LLM-based agents to accelerate pipeline development and automate data quality tasks.

What we're looking for

• 6+ years of full-time experience in Data Engineering, Analytics Engineering, Business Intelligence Engineering, or a related analytical role.
• Proficiency in SQL including complex query optimization and data modeling.
• Proficiency in Python for data pipeline development.
• Experience with distributed data frameworks like Spark to write and debug data pipelines.
• Experience with workflow orchestration tools such as Airflow, Flyte, or equivalent.
• Proven ability to design, implement, and maintain production-grade data pipelines and dashboards.
• Good understanding of development processes including engineering standards, code reviews, and testing.
• Ability to communicate results and drive impact with cross-functional partners.