Senior Data Engineer for Embedded Analytics & Observability

Luxoft; Göteborgs kommun; On-site; SEK 900,000 - 1,200,000; Full time

Job summary

Luxoft in Sweden is seeking a Senior Data Engineer to join an automotive observability project. You will design and operate data pipelines, model data and build analytics-ready datasets to support rapid troubleshooting and reliability analysis.

You will work with logs, events, telemetry and time-series data from embedded, cloud, test and application sources, implementing data-quality checks and monitoring while enabling dashboards and stakeholder insights.

Qualifications

• Experience building production-grade data pipelines.
• Proficient in Python and SQL.
• Strong data modelling and transformation knowledge.
• Experience with cloud-based data solutions.
• Experience with data orchestration and workflows.
• Experience with APIs, event data and logs.
• Experience with data quality and pipeline monitoring.
• Experience with high-volume time-series and telemetry data.

Responsibilities

• Design, build and maintain production-grade data pipelines and transformations.
• Develop data models, schemas and curated datasets for different engineering use cases.
• Process logs, events, telemetry and high-volume time-series data.
• Integrate data from embedded, cloud, test and application sources using APIs and other data interfaces.
• Implement automated data-quality checks and pipeline monitoring.
• Build analysis-ready datasets supporting troubleshooting, reliability and product-quality analysis.
• Improve pipeline reliability, performance and maintainability.
• Support dashboards and analytical use cases.
• Document delivered solutions and support knowledge transfer.

Skills

Data pipelines

Python

SQL

Data modelling

Cloud data solutions

Data orchestration

APIs & logs

Data quality monitoring

Time-series data

Job description

Luxoft in Sweden is seeking a Senior Data Engineer to join an automotive observability project. You will design and operate data pipelines, model data and build analytics-ready datasets to support rapid troubleshooting and reliability analysis.

You will work with logs, events, telemetry and time-series data from embedded, cloud, test and application sources, implementing data-quality checks and monitoring while enabling dashboards and stakeholder insights.