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).