DATA ENGINEER - Stockholm / Remote

The data engineer is in charge of implementing end-to-end data transformations from ingestion to consumption, as well as ensuring a governed and structured use-cases consumption area. A strong emphasis should be placed on data and code quality, improving functional and non-functional requirements, and ensuring scalable and performant processes while leveraging PaaS and IaaS components.
Responsibility
Data architecture
Develop data requirements and activities requested by use cases in a structured, performant manner, while improving data quality and leveraging the solution architecture.
Connect to data sources securely, understand their limitations and data assets, and ingest data from them to our main storage components.
Metadata is stored and maintained to improve transparency and the execution of idempotent routines.
Recognize and implement data architecture design
Provide feedback and confirm the feasibility of the data architecture design.
Software Engineering
Create applications and components that make use of design patterns and practises, resulting in a codebase that is extensible and maintainable.
Ensure high code quality while improving secure and bug-free features for use-cases and clients.
Utilize Azure and cloud-native components to ensure that data processing activities are carried out as efficiently as possible.
Use-cases support
Collaborate closely with use cases to gather and develop feature requirements and data asset availability.
Maintain SLAs in the event of a failure and assist with hotfix and bugfix development as soon as possible.
Through workshops and knowledge sharing sessions, assist use-cases with exploration and machine learning capabilities.
Focus
Support for data architecture,
Software engineering,
Use-cases Support
Qualifications
Extensive knowledge of software engineering principles
Excellent knowledge of data quality measures
Knowledge of Azure Data Factory, Azure Data Lake, Databricks and Spark, and Apache Airflow is required.
Python development experience Data modelling experience
Best practises and knowledge of cloud-native architectures
Extensive knowledge of Azure's PaaS and IaaS offerings
KPIs
Story points accomplished per sprint
Completion of sprint goals On-time
# of bugs and defects post-release
Use case satisfaction with development and support
Completion of sprint goals on time
Duration: 6 months + extension
Location: Stockholm / Remote
Looking forward to your applications.