Senior Data Engineer: Telemetry & Observability Pipelines

Luxoft; Kraków; Vor Ort; PLN 180.000 - 240.000; Vollzeit

Zusammenfassung

Luxoft is seeking an experienced Senior Data Engineer to join a project focused on observability and embedded analytics for an automotive client. You will build production data pipelines, transform logs and telemetry, and create analysis-ready datasets for troubleshooting and product-quality insights.

The role involves hands-on data modeling, API integration and data quality monitoring across embedded, cloud and test sources, with a focus on high-volume time-series data.

Qualifikationen

• Proven track record building production data pipelines.
• Strong Python and SQL hands-on experience.
• Experience with cloud-based data solutions.
• Experience with data orchestration and automated workflows.
• Experience with APIs, event data and logs.
• Familiarity with high-volume time-series or telemetry data.

Aufgaben

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

Kenntnisse

Python

SQL

Data pipelines

Data modeling

Cloud data solutions

APIs & data interfaces

Data quality & monitoring

Time-series data

Tools

Airflow

Jobbeschreibung

Luxoft is seeking an experienced Senior Data Engineer to join a project focused on observability and embedded analytics for an automotive client. You will build production data pipelines, transform logs and telemetry, and create analysis-ready datasets for troubleshooting and product-quality insights.

The role involves hands-on data modeling, API integration and data quality monitoring across embedded, cloud and test sources, with a focus on high-volume time-series data.