Data Engineer, Real-Time Energy Platform

WERAANBIEDING UIT EEN ANDERE REGIO; Vilvoorde; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Flexible hybrid/remote options

Competitive salary

Growth opportunities

Job summary

MegaCharge is building an EMS data backbone and seeks a Data Engineer to design and run pipelines, storage and data models feeding optimization, forecasting and ML models. You will collaborate with R&D and hardware teams to ensure robust, scalable data flows for real-time and historical analysis.

You will contribute to data quality, observability and governance while supporting production deployments and documentation.

Qualifications

• Strong Python and SQL.
• Proven experience building data pipelines (batch and/or streaming) in production.
• Experience with time series data.
• Experience with a cloud data stack (e.g. GCP, BigQuery, Pub/Sub or equivalent).
• Solid data modeling and schema discipline.
• Knowledge of logging, monitoring and observability.
• Familiarity with orchestration and transformation tools (e.g. Airflow, Dagster, dbt).
• Git/GitLab and solid documentation habits.
• Genuine interest in the energy transition.

Responsibilities

• Design, build and maintain batch and streaming data pipelines.
• Model, store and serve high-volume time series data.
• Maintain clean, versioned schemas and data contracts.
• Implement data quality validation, anomaly detection and alerting.
• Monitor pipeline health, latency and costs; support dashboards.

Skills

Python

SQL

Data pipelines

Time series data

Cloud data stack

Data modeling

Monitoring/Observability

Git/GitLab

Communication

Tools

Airflow

Dagster

dbt

Grafana

BigQuery

Pub/Sub

Docker

Job description

MegaCharge is building an EMS data backbone and seeks a Data Engineer to design and run pipelines, storage and data models feeding optimization, forecasting and ML models. You will collaborate with R&D and hardware teams to ensure robust, scalable data flows for real-time and historical analysis.

You will contribute to data quality, observability and governance while supporting production deployments and documentation.