Senior Data Engineer - Lakehouse & Streaming Pipelines (Hybrid)

Etraveli Group; Uppsala kommun; Hybrid; SEK 650,000 - 900,000; Full time

Benefits offered by this job

Hybrid work model

Healthcare allowance

Pension and health insurance

Daily breakfast

Hackathons and Dev Weeks

Personal development

Job summary

Etraveli Group is seeking a skilled Data Engineer to join the Data Platform team in Gothenburg. You will design and maintain batch and streaming pipelines, ingest diverse data sources, and ensure data quality and performance across our modern lakehouse architecture.

Collaborate with ML engineers, backend teams, and stakeholders to translate business needs into robust data products and scalable solutions that support pricing, analytics, and decision making.

Qualifications

• 5+ years of experience in data engineering or a comparable technical role.
• Strong foundation in data warehousing concepts and data model translation.
• Hands-on experience building batch and streaming pipelines.
• Proficiency in SQL and programming languages (Python, Scala, Bash).
• Experience with Lakehouse architectures and object storage (S3/Ceph).
• Familiarity with Kafka and CDC tools; comfortable with Linux, Docker, Kubernetes.

Responsibilities

• Design, develop, and maintain robust batch and streaming pipelines.
• Ingest data from cloud and on-prem sources into the data lakehouse platform.
• Evaluate and integrate frameworks and tooling for scalable data engineering.
• Define and enforce data quality standards with monitoring and alerting.
• Collaborate with ML engineers, backend developers, DBAs, and stakeholders to prioritize data needs.
• Ensure high-performance data processing and efficient data modeling.
• Promote best practices and continuous learning within the team.

Skills

Data engineering

SQL

Python

Scala

Airflow

Tools

Spark

dbt

Dremio/Trino

Databricks

Job description

Etraveli Group is seeking a skilled Data Engineer to join the Data Platform team in Gothenburg. You will design and maintain batch and streaming pipelines, ingest diverse data sources, and ensure data quality and performance across our modern lakehouse architecture.

Collaborate with ML engineers, backend teams, and stakeholders to translate business needs into robust data products and scalable solutions that support pricing, analytics, and decision making.