Data Engineer
Ballerup, DK
Do you have a passion for data and a desire to work with cutting-edge tools and technologies? Join our CX Technology team and leave your mark on both internal and customer-facing applications!
About us | The CX Technology Team
Data is one of the most important assets for Tryg, and customer experience is one of the key strategic pillars for our entire business. You will work at the intersection of both!
You will be part of the CX Technology team in Tryg's Data & Analytics division. The team has Nordic responsibility for managing and supporting all technical aspects of the Customer Experience/Voice of the Customer platform in Tryg Group, from data modelling and integrations to compliance and vendor relations.
Together with awesome colleagues, you will contribute directly to Tryg’s newly launched “United Towards ’27” strategy and impact both internal and customer-facing applications.
About the job | Data Engineer
Data engineering plays a critical role in our CX journey, as we integrate with ever more systems/sources, implement streaming data, and standardize raw data through data modelling.
Customer engagement data is scattered across a multitude of different systems, and to work with customer experience processes at scale, we have built a modern foundation based on open source, cloud-native, and real-time data platform for easy, purpose-driven, and compliant access to data from those systems.
In your role as our new Data Engineer, you will work with cutting-edge tools and technologies on building and maintaining data pipelines for the CX domain sources and applications in the data platform. You will be given responsibility for tasks such as:
- Deconstruct and “understand” data from source systems through an end-to-end ETL process
- Development and maintenance of CX data pipelines, as well as development of foundational CX application components
- Coordinate efforts of the extended team of both in-house and external developers, and follow up on technical/infrastructure changes with our Platform team
- Ensure code quality across all CX applications, including compliance with established DevOps principles
- Coordinate ingestion of raw data from new streaming and API-based data sources
- Development of AI and ML components for internal use cases
- Work on custom integrations to and from both 1st and 3rd party systems
As a data engineer in Tryg, you will mainly be working with technologies such as Java, Python, SQL, GraphQL, Kafka, Kubernetes, GitLab CI/CD, and REST APIs, and we expect you to be familiar with at least some of them.
About you | Curious and learning-oriented
We expect you to have a relevant education in software engineering, data engineering, data science, data management, or similar.
Our data engineering tech stack is heavily focused around Kafka and streaming. It is a definite advantage if you can demonstrate experience in that area, but experience as a software engineer or data scientist, genuine curiosity, and a desire to invest in your development can compensate for a lack of experience with streaming. If you have only worked with Java or Python development and batch processing but want to expand your skillset with streaming – we'd still love to hear from you!
You take the initiative to solve problems and get things done. You see technical challenges as an exciting new obstacle to overcome, and a reason to improve your skills. To be successful in the role you must be self-driven and strive to challenge the status quo.
The team is scattered across several countries, so you communicate clearly in English, and preferably also in a Scandinavian language, both verbally and in writing.
Curious?
Please send your application as soon as possible, but no later than the 12th of January, as we will conduct interviews continuously.
If you have any questions regarding the role, you are welcome to contact Head of CX Technology, Pavel Kruglov at pavel.kruglov@tryg.no
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs CI/CD CX Data management Data pipelines DevOps Engineering ETL GitLab GraphQL Java Kafka Kubernetes Machine Learning Open Source Pipelines Python SQL Streaming
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