Senior Software/Data Engineer
Fuld tid
Saxo Bank
Copenhagen, Denmark About The Job Do you want to work with data engineering, platform development, and data-based automated processes within Saxo's Financial Crime Prevention (FCP)? Saxo is an investment bank with high speed, global colleagues, and a strong focus on using technology and data to prevent financial crime. We are looking for a Senior Software/Data Engineer to join the FCP Modelling & Development team. FCP Modelling & Development is part of the 1st Line of Defence in Group Operations and is located in Saxo's headquarters in Hellerup. The team works with models and data-based automated processes used across FCP. The goal is to ensure that these data assets and processes are sound, fit for purpose, adequately documented, secure, and regularly reviewed. Responsibilities
- Build, operate, and continuously improve reusable AML data products, data-modelling components, and user-facing interfaces, with clear ownership, lineage, documentation, quality controls, and production reliability.
- Design robust ETL pipelines and integration interfaces for operational, analytical, model-development, and external-platform use cases, enabling secure and efficient data exchange across internal and external systems.
- Translate FCP and AML requirements into durable, adaptable production systems, contributing to solution architecture decisions on design patterns, system scalability, regulatory compliance, and flexibility across AML processes.
- Partner with FCP and AML subject-matter experts on transaction monitoring, customer segmentation, scenario development, client risk rating, surveillance support, and AML-related development initiatives that strengthen financial crime prevention capabilities.
- Define automated checks for completeness, consistency, validity, reconciliation, source-to-target integrity, architectural integrity, security, performance, and governance standards.
- Own observability, alerting, incident response, backfills, runbooks, performance tuning, production support, and operational resilience for critical data assets.
- Raise engineering standards through design and code reviews, mentoring, reusable patterns, clean and well-documented code, test-driven development, secure coding practices, CI/CD pipeline optimization, automated testing, and continuous improvement.
- 5+ years of experience in data engineering, software engineering, data-platform engineering, or a related production data role.
- Strong Python, SQL, and Spark skills, with experience building and maintaining production data pipelines and data models.
- Practical experience with modern data platforms such as Databricks, Kafka, Snowflake, Airflow, Azure, or similar technologies.
- Experience supporting ML workflows, including feature engineering, feature data preparation, dataset versioning, reproducible training and validation datasets, model-validation support, and production-ready model inputs.
- Deployment skills for production workloads, including CI/CD, containerized services, and Kubernetes or similar orchestration platforms.
- Strong understanding of authentication, authorization, data access controls, encryption, secure handling of sensitive data, and practical data-security patterns using Azure services such as Microsoft Entra ID, Azure Key Vault, Azure RBAC, and Managed Identities.
- Hands-on experience maintaining production data pipelines, including data quality testing, reconciliation, lineage, metadata management, documentation, monitoring, and operational controls.
- Experience with financial crime prevention in regulated financial services, including AML, KYC/CDD/ODD, sanctions screening, transaction monitoring, client risk rating, and market-abuse surveillance support.
- Experience with GDPR-sensitive data, audit evidence, regulator-facing reporting, or data governance in control-heavy environments
- Experience with data quality validation tools e.g. Great Expectations (GX), dbt‑expectations, Soda, Deequ, or Microsoft Fabric.
- Clear communication in English with technical and non-technical stakeholders.
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