Risk Data Analyst
Santander
Posted: February 25, 2026
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Quick Summary
As a Risk Data Analyst in our Oslo team, you will be responsible for validating and delivering high-quality risk data for our business operations, ensuring accuracy, traceability, and audit-readiness.
Required Skills
Job Description
Risk Data Analyst
Country: Norway
Risk Data Analyst
Join our Risk Data Team in Oslo!
Do you enjoy turning complex data into something people can trust and act on? As a Risk Data Analyst, you’ll be the link between business needs and data delivery—making sure risk data used in models and regulatory reporting is accurate, traceable, and audit-ready. You’ll also be part of our journey moving from on‑prem SQL Server to AWS (S3/Iceberg + Spark/EMR Serverless), helping shape how we build and validate risk data going forward.
If you thrive on detail, like solving messy problems, and enjoy bridging technical and business worlds—we’d like to hear from you.
What this role is about
The Risk Data team owns the data repositories used for risk models and regulatory reporting. This role is for someone who enjoys being the link between business stakeholders and data delivery teams—turning requirements into build‑ready specifications, and making sure every release is accurate, traceable, and audit‑ready.
We’re also moving part of our data warehouse from on‑prem SQL Server to AWS (S3/Iceberg + Spark/EMR Serverless). You’ll be part of that journey, with a strong focus on data quality and controls.
Key responsibilities
• Requirements intake & scoping: clarify the change request, purpose, success criteria, and what “done” looks like
• Business process understanding: learn how risk processes (credit lifecycle, collections/recoveries, impairment/provisioning, regulatory capital) translate into data and controls
• Business analysis & rule definition: drive structured discussions, remove ambiguity, capture edge cases, define acceptance criteria
• Write build‑ready specs: source‑to‑target mapping, keys/joins, transformation rules, defaults; use (pseudo‑) SQL where it helps
• Impact analysis / lineage thinking: assess downstream impacts and propose safe rollout/fallback options
• Data quality controls: define validations, reconciliations, and data‑quality KPIs; design UAT scenarios and capture audit evidence
• Documentation & traceability: maintain data dictionary, business definitions, variable catalogue, lineage, and change log
• Incidents & root cause: triage issues, identify root cause, specify fixes and preventive controls, track to closure
• Release cadence: contribute to a monthly delivery cycle (plus urgent fixes when needed)
Required skills / must‑haves
• Strong SQL (required): complex joins, CTEs, window functions, and debugging transformation logic
• Comfortable translating business/regulatory needs into clear technical requirements and test cases
• Able to communicate well with both technical and non‑technical stakeholders
• Solid written/spoken English
• Detail‑oriented: you care about definitions, evidence, and “what changes what” (traceability)
Skills and personal traits required to succeed
• Comfortable working independently and in teams, switching between leading and supporting when needed
• Strong problem‑solving skills and good judgement under time pressure
• Curious, with attention to detail, and you take pride in delivering high‑quality work
• Organized and structured—able to execute on plans and tasks and keep documentation/evidence in order
• Flexible and service‑oriented in terms of going the extra mile when required
Nice‑to‑haves / beneficial
• Python (useful for validation, reconciliation, automation)
• Familiarity with data warehousing and data modelling concepts (dimensional modelling, keys, grain, etc.)
• Exposure to IFRS 9, Basel, and/or IRB topics
• Interest in modern tooling, including AI‑assisted workflows—using tools to move faster without compromising controls or auditability
• Familiarity with SAS (used in parts of the environment)
Tech environment (current + evolving)
• On‑prem: SQL Server / T‑SQL
• AWS (migration ongoing): S3 + Iceberg, EMR Serverless / Spark
• Additional tooling used across teams: SAS, Python; PySpark expected to become more relevant
Experience & education
• Bachelor’s or Master’s in a relevant field (technology, statistics, mathematics, finance, etc.)
• 1–4 years in data‑heavy roles; experience with risk data, rule engines, and/or database management is valued
Practical information
• Position type: Full‑time
• Location: Oslo
• Working model: Hybrid (typically 3 days/week in the office)
• Work permit: Applicants must have a valid work permit in Norway
Interested?
Submit your application as soon as possible and no later than March 15, 2026.
If you have questions or want more information about this position, feel free to contact: Myurathan Kajendran, Risk Data Leader, Email: [email protected] or mobile: +4745031079
We perform background checks on all relevant candidates. For positions that require authorization and/or confirmation of suitability, a police certificate of good conduct and credit check must be presented. Background checks are carried out with prior consent from the candidate.