Senior Data Engineer for Credit Data Solutions Squad

AWS Data Engineer ETL Python Risk SQL

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We believe taking risks is crucial in banking, and we’re committed to changing how we handle them. This is your opportunity to make a real impact on your personal and professional journey. Risk & Compliance Tribe brings together business and IT professionals into cross-functional squads and enables us to work in a truly agile organisation. Each of these squads are self-organized teams empowering its employees to take their own decisions while working on the end-to-end delivery of products and services.

As a Senior Data Engineer, you will become a vital member of the Credit Data Solutions Squad within the Risk and Compliance Tribe. In this role, you will leverage your technical expertise to design and develop data solutions that are crucial for facilitating data-driven credit risk insights and reporting. The squad plays a pivotal role in managing and delivering data through our Data Warehouse, thereby supporting the organisation’s analytical and decision-making capabilities.

Additionally, you will be part of the Data Engineers chapter, a community of highly skilled engineers who share your passion for data and technology. The chapter promotes continuous learning and knowledge sharing, ensuring best practices are disseminated across the tribe and organisation.

You will:

Design, developing and implementing end-to-end data solution
Understand how data is extracted, transformed and loaded for BI purposes, how it influences decision modelling and the overall risk management
Drive the optimization and automatization of the existing flows and processes in the systems
Collaborate with other Data Engineers in the chapter, you will build a solution for reliable, robust and easily accessible risk data repository
Consult other engineers, data scientists and analysts from other areas in the bank on risk data related questions
Be a part of agile organization driving the transformation and improving the ways we do Risk management in the bank

About you:

At least 5 years of experience as a Data Engineer or in a similar role, with a solid understanding of ETL processes and data modelling
Extensive hands-on experience with SQL, including T-SQL/PL-SQL
Advanced proficiency in Python/PySpark for data engineering tasks
Familiarity with Cloud technologies, preferably AWS, and experience with infrastructure management using Infrastructure as Code (IaC) tools
Experience with CI/CD pipelines
Ability to see the broader picture while effectively understanding detailed data usage, dependencies, and relationships
Strong written and verbal communication skills in English, with the ability to clearly explain IT concepts to non-technical colleagues
Preferred academic background in Computer Science, Statistics, Physics, or Mathematics
Genuine interest in the risk area
Advanced English skills

We offer:

Monthly salary range from 4560 EUR to 6840 EUR gross (based on your competencies relevant for the job).

Additionally, each Danske Bank employee receives employee benefits package which includes:

Growth opportunities: professional & supportive team, e-learnings, numerous development programs; (incl. professional certificates); 100+ professions for internal mobility opportunities.
Health & Well-being: a diverse, inclusive, work & life balance work environment; additional health insurance; mental well-being practices; partial psychologist counselling compensation; silence and sleep zones at the office; game rooms.
Hybrid working conditions: Work from home up to two days a week; home office budget (after the probation period); modern Danske Campus workplace developed with anthropologist for the best employee experience.
Additional days of leave: for rest, health, volunteering, exams in higher education institutions, and other important activities. Moreover, for seniority with Danske Bank.
Monetary compensation package: accidents & critical diseases insurance; financial support in case of unfortunate events, travel insurance; IIIrd Pillar Pension Fund contribution.