Senior Data Engineer for Data Products

Data Databricks Engineering LT

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Do you have passion for data and want to help building innovative data products? Do you enjoy creating scalable solutions and view highly regulated environments as exciting challenges? Do you want to play an important role in Danske Bank’s transition to a decentralized data products paradigm?

Data Product Solutions squad is part of the Data Platform Tribe, which supports data professionals across Danske Bank.

You will have the opportunity to join us at the early stages of this journey, collaborating on the design and implementation of data product solutions that drive business value. You will work alongside experienced professionals who are passionate about data engineering.

Our team values continuous learning, knowledge sharing, and the adoption of new technologies to address complex data challenges. Our squad focuses on architecting and building data products and pipelines in Databricks, using tools such as SQL, PySpark, and Databricks LakeFlow Declarative Pipelines.

Depending on your experience, you may be offered a different seniority of the role.

Danske Bank supports a high degree of workplace flexibility; our team currently uses a hybrid working model, working at least three days a week in the office.

You will:

Design and develop: Architect and implement scalable, robust data products and pipelines, ensuring efficient and reliable solutions that follow best practices in data modeling
Data quality: Implement data validation checks, data governance and security standards, monitoring systems, and automated testing frameworks to maintain high data quality
Collaboration: Partner with cross-functional teams to deliver business-focused solutions
Optimization: Improve pipeline performance and reliability using industry best practices
Continuous learning: Keep up with new technologies and methods in data engineering

About you:

4+ years of hands-on experience in designing and implementing data solutions
Proficiency: Strong expertise in SQL and Python/PySpark for complex data manipulation and developing scalable ETL processes
Cloud technologies: Experience in cloud engineering environments and familiarity with modern platforms such as Databricks, AWS or Azure
Version control and CI/CD: Familiarity with CI/CD pipelines and version control tools like GitHub or Azure DevOps. Experience with setting up CI/CD pipelines is an advantage
Data modelling and orchestration: A solid understanding of data modelling and pipeline orchestration
Additional expertise: Experience with Databricks Asset Bundles (DAB) and Databricks Repos is a plus
Soft skills: Strong interpersonal, problem-solving, decision-making and conflict resolution abilities
Advanced English skills

Even if you do not meet all the requirements, we encourage you to apply – we value potential and are eager to hear from motivated candidates.

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.