Credit Data Engineer

What You’ll Do

• Own the global UW tables (canonical facts/dimensions for applications, decisions, features, repayments, delinquency) with clear SLAs for freshness, completeness, accuracy, and data lineage.
• Design for AI‑agents and humans: consistent IDs, canonical events, explicit metric definitions, rich metadata (schemas, data dictionaries), and machine‑readable data contracts.
• Build & run pipelines (batch + streaming) that feed UW scoring, real‑time decisioning, monitoring, and underwriting optimization.
• Instrument quality & observability (alerts, audits, reconciliation, backfills) and drive incident/root‑cause reviews.
• Partner closely with Credit Portfolio Management, Policy teams, Modeling teams, and treasury and finance teams to land features for RUE and consumer‑centric models, plus regulatory and management reporting.

Tech Stack (what We Use)

• Languages: SQL, PySpark, Python
• Frameworks: Apache Airflow, AWS Glue, Kafka, Redshift
• Cloud & DevOps: AWS (S3, Lambda, CloudWatch, SNS/SQS, Kinesis), Terraform; Git; CI/CD

What You’ll Bring

• Proven ownership of mission‑critical data products (batch + streaming).
• Data modeling, schema evolution, data contracts, and strong observability chops.
• Familiarity with AI/agent patterns (agent‑friendly schemas/endpoints, embeddings/vector search).