Social Finance - Jacksonville, FL

posted about 1 month ago

Full-time - Senior
Remote - Jacksonville, FL
Religious, Grantmaking, Civic, Professional, and Similar Organizations

About the position

The Data Manager for Risk Engineering & AI at SoFi is a senior-level role focused on developing data-intensive solutions to enhance data-driven decision-making within the Independent Risk Management function. This position involves collaborating with senior leadership to identify opportunities for innovative data and AI solutions, ultimately shaping risk oversight strategies. The role requires hands-on experience in data engineering, API development, and collaboration with AI/ML teams to implement enterprise-grade data processing pipelines.

Responsibilities

  • Design, develop, and maintain scalable and efficient data pipelines to ingest, process, and store diverse data sets.
  • Perform data cleaning, validation, and transformation to prepare high-quality data sets for analytics and reporting.
  • Build and manage data staging environments and ensure optimal storage of structured and unstructured data.
  • Create and maintain APIs to expose data for internal teams, ensuring secure and reliable data access.
  • Collaborate with AI/ML specialists and risk financial reporting analysts to deploy data processing pipelines to production.
  • Implement best practices for data governance, including data lineage, versioning, and monitoring.
  • Identify areas for process improvement, automation, and optimization within the data pipeline.

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • Minimum of 8+ years of experience in data engineering or a related role.
  • Expert proficiency in Python for data manipulation and transformation.
  • Strong experience in querying database schemas using advanced SQL.
  • Deep hands-on experience with core technologies such as Snowflake, Airflow, dbt, git, docker, Tableau, and Streamlit.
  • Experience with relational and NoSQL databases and data lakes.
  • Familiarity with large language models (LLMs) and their integration into data pipelines.

Nice-to-haves

  • Prior experience in working with machine learning teams and AI-based solutions deployment.

Benefits

  • Comprehensive and competitive benefits package including health insurance, retirement plans, and paid time off.
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