Analytics Engineer

In this role you will design, build, and maintain production grade data models and pipelines that support regulatory reporting analytics and AI workflows. You will implement data quality checks and data contracts, fix data gaps with upstream teams, and ensure data accuracy for live regulatory exams and audits. You will automate recurring workflows into scalable pipelines and provide clear documentation. You will participate in on call triage and root cause analysis.

Responsibilities

• Design, build, and maintain production grade data models and pipelines that cover user, transaction, and compliance data across retail and institutional product lines
• Build data quality checks, data contracts, validation logic, and monitoring to protect the integrity of the foundations before issues propagate into regulatory reports or downstream workflows
• Partner with upstream engineering teams to fix data gaps and absorb product changes at the source, owning data issues anywhere in the stack
• Support live regulatory exams, audits, and regulator requests with accurate, timely data
• Automate recurring manual workflows into scalable pipelines and self serve tooling
• Perform front line on call duties, triage pipeline incidents, contribute to root cause analysis, and maintain clear technical documentation and runbooks

Requirements

• 2+ years of experience building and maintaining production data pipelines and data models, with daily proficiency in SQL, Python (scripting, automation, OOP), dbt, Airflow, and modern warehouse architecture (Snowflake or Databricks)
• Demonstrated experience with data modeling patterns (star snowflake schemas, OBTs, SCDs) and building certified or canonical data models that serve multiple downstream consumers
• Track record implementing data quality frameworks including data contracts, validation logic, reconciliation, and monitoring to catch issues before they reach downstream reports
• Experience supporting time sensitive, high stakes data needs (regulatory exams, audits, or financial reporting) while maintaining accuracy standards under pressure
• Proven ability to work independently, scoping and driving foundational data work end to end without waiting for direction, and converting tribal knowledge into durable, documented infrastructure
• Utilizes generative AI responsibly, maintaining human oversight to deliver business ready outputs and drive measurable improvements in workflow efficiency, cost, and quality