Senior Data Engineer - End-to-End Pipelines & Lakehouse

Digitalenta; Malmö kommun; On-site; SEK 900,000 - 1,300,000; Full time

Benefits offered by this job

Healthcare allowance

Insurance policy

Paid vacation days

Pension savings

Consultant manager

Networking activities

Job summary

Digitalenta is seeking a senior data engineer to design, build and maintain automated, scalable data solutions for performance evaluation products used by customer meeting points and franchisees. You will connect data from multiple sources into a unified framework, ensuring accuracy and auditability across the analytics ecosystem.

You will work with Databricks, Spark and Delta Lake in lakehouse architectures on Azure Data Lake Storage, applying DevOps practices, CI/CD, testing and IaC to deliver

Qualifications

• Senior data engineer with end-to-end pipeline design and implementation.
• Hands-on with Databricks and Spark in lakehouse environments.
• Strong knowledge of Azure Data Lake Storage and DevOps practices.
• Experience with data governance, validation and auditing.

Responsibilities

• Design, build and maintain automated, scalable data solutions for performance evaluation products.
• Create the data foundation that enables reporting, analytics, governance and future scalability.
• Connect data from multiple sources into a unified framework for evaluation across multiple criteria.
• Ensure accuracy, data validation, version control and auditability.

Skills

Databricks

Apache Spark

Delta Lake

Lakehouse architecture

Data modelling

Azure Data Lake Storage

End-to-end data pipelines

Git

CI/CD pipelines

Infrastructure as code

Tools

Git

CI/CD

Automated testing

Infrastructure as code

Azure Data Lake Storage

Job description

Digitalenta is seeking a senior data engineer to design, build and maintain automated, scalable data solutions for performance evaluation products used by customer meeting points and franchisees. You will connect data from multiple sources into a unified framework, ensuring accuracy and auditability across the analytics ecosystem.

You will work with Databricks, Spark and Delta Lake in lakehouse architectures on Azure Data Lake Storage, applying DevOps practices, CI/CD, testing and IaC to deliver