Senior Data Engineer, Risk

You Will

• Lead the creation and optimization of existing data models through AI code generation on eventing, customer level, and process level data.
• Standardize business and product metric definitions in curated and optimized datasets, and develop data dictionaries and other related documentation.
• Build monitoring to assess data quality and lineage and on top build AI agents for false positive reduction and automated resolution.
• Participate in on-call rotation, monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with internal stakeholders. Automate this process through AI agents to focus human effort on highest priority tasks.
• Work with non-technical partners and product teams to understand their needs, translate business requirements into applicable data requirements, and come up with automated end-to-end solutions.

You Have

• A minimum of 10 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or equivalent experience.
• High proficiency in SQL, Python, and Dbt
• Experience designing medium-to-large data engineering solutions and responsible for the entire lifecycle of projects including scoping, design, development, testing, deployment, and documentation
• Experience with ETL scheduling technologies with dependency checking, such as Airflow or Prefect
• Experience in schema design and dimensional data modeling
• Experience with setting up data quality and data lineage monitoring
• Experience with data driven decisions through AI and agentic automation

Technologies We Use and Teach

• Snowflake
• Databricks
• Dbt
• Github
• Airflow
• Prefect
• Omni
• Terraform