Credit Data Engineer Engineering · Stockholm · Full-time · kr 752,814 SEK - kr 843,151 SEK

Deel; Stockholms kommun; Hybrid; SEK 669,600 - 837,000; Full time

Job summary

A data management firm in Sweden is seeking a skilled data product owner to oversee mission-critical data products. The role involves managing global data tables, designing data structures for AI agents and humans, and collaborating with various teams on features related to underwriting and decision-making. Ideal candidates should have strong skills in SQL, Python and proven experience in observability and data modeling. This position involves running pipelines for real-time decisioning and ensuring data quality.

Qualifications

• Proven ownership of mission-critical data products (batch + streaming).
• Strong skills in data modeling, schema evolution, and observability.
• Familiarity with AI/agent patterns (schemas/endpoints, embeddings/vector search).

Responsibilities

• Own the global UW tables with clear SLAs for freshness and accuracy.
• Design data structures for AI-agents and humans.
• Build and run pipelines for UW scoring and decisioning.
• Drive incident/root-cause reviews and ensure quality observability.
• Collaborate with various teams for feature implementation.

Skills

Data product ownership

SQL

PySpark

Python

Data modeling

Observability

Job description

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

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).