Finance Staff Data Engineer, AI Native in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Finance Staff Data Engineer, AI Native in United States.

This is a high-impact engineering role at the intersection of finance, data platforms, and AI-driven development. You will be responsible for designing and evolving the core data infrastructure that powers financial reporting, accounting workflows, and compliance-critical systems at scale. Working within a modern, AI-native engineering environment, you will build and optimize data ingestion, transformation, and egress frameworks that support high-volume, production-grade financial data flows. The role requires strong architectural thinking, with a focus on scalability, reliability, and developer efficiency across the entire data lifecycle. You will also play a key role in integrating AI tools into engineering workflows to accelerate delivery and improve system intelligence. This position is ideal for a senior engineer who thrives in complex, distributed systems and enjoys shaping foundational data platforms.

• Architect and evolve scalable data ingestion, transformation, and egress frameworks for financial data systems.
• Design and maintain robust pipelines ensuring high data quality, reliability, and observability across all workflows.
• Build and enhance CI/CD pipelines, improving testing, deployment automation, and developer velocity.
• Develop and optimize data infrastructure across AWS, Databricks, and related cloud environments.
• Define and enforce data security, governance, and SOX compliance controls across systems.
• Implement distributed data processing systems using Spark and modern cloud data architectures.
• Improve developer experience through tooling, automation, and AI-assisted engineering workflows.
• Establish ingestion standards, monitoring systems, and recovery mechanisms to ensure system resilience.
• Collaborate with analytics engineers and finance stakeholders to support downstream reporting and modeling.
• Leverage AI/LLM tools to accelerate development, debugging, and system optimization while maintaining quality ownership.
• Identify architectural risks, dependencies, and scalability challenges, providing clear technical direction.
• Mentor engineers and contribute to raising engineering standards across the team.

• 8+ years of experience building and operating large-scale distributed data systems in production environments.
• Strong expertise with cloud platforms, ideally Databricks, and AWS infrastructure/services.
• Advanced proficiency in Python, SQL, and Spark for large-scale data processing.
• Strong experience with CI/CD pipelines, Terraform, and modern DevOps practices.
• Solid understanding of dbt, data modeling, and analytical data architecture.
• Experience with data orchestration tools such as Airflow.
• Deep knowledge of data ingestion challenges including networking, APIs, and cross-cloud integration.
• Strong systems design skills with experience in scalable and event-driven architectures.
• Proven ability to use AI/LLM tools (e.g., Cursor, Claude, GitHub Copilot-style tools) to enhance engineering productivity.
• Experience implementing data quality controls, validation frameworks, and observability systems.
• Ability to independently scope ambiguous technical problems and drive them to completion.
• Strong communication skills across technical and non-technical stakeholders.
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent experience.

• Competitive compensation package including base salary and equity opportunities.
• Comprehensive health benefits (medical, dental, vision, life, and disability coverage).
• Retirement savings plans with company contributions (401k/RRSP equivalents depending on location).
• Flexible paid time off and company-wide holidays.
• Fully remote-first working environment with home office equipment support.
• Learning and development programs to support technical growth.
• Mental health and employee assistance programs.
• Access to advanced AI tools and modern engineering environments.