> Markdown version of [/jobs/ext/3719850-data-engineer](https://www.wearedevelopers.com/jobs/ext/3719850-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer

- **Company:** MEGACHARGE
- **Location:** Vilvoorde, Belgium
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, BigQuery, Cloud Computing, Cloud Database, Software Quality, Data Architecture, Data Governance, Data Visualization, Monitoring of Systems, Identity and Access Management, Python (Programming Language), Machine Learning, Modbus, Message Queuing Telemetry Transport (MQTT), SQL Databases, Data Streaming, Transmission Control Protocol (TCP), Data Logging, Google Cloud, Time Series Databases, Grafana, Backend, Gitlab, Git, Fastapi, Data Layers, Gitlab-ci, Influxdb, Optimization Algorithms, Machine Learning Operations, Terraform, Data Pipelines, Docker
- **Published:** October 14, 2026
- **Apply:** https://europa.eu/eures/portal/jv-se/jv-details/NzY0NzU1ZWYtNjI0MS00ZWQxLTg5ZDktZWUyMTg1YjBjOTE1IDM?lang=en

## About the Role

* 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.

Nice-to-have

 * Experience with time series databases (e.g. TimescaleDB, InfluxDB).
 * Exposure to Modbus TCP, OCPP or MQTT protocols, or energy/IoT systems.
 * Knowledge of ML workflows (feature pipelines, MLOps) and forecasting.
 * Experience with Grafana or other data visualization tools.
 * Familiarity with FastAPI or other backend frameworks.
 * Experience with Docker, Terraform or infrastructure as code.
 * Exposure to cybersecurity and data governance best practices.
 * Knowledge of energy market data (day-ahead, intraday, balancing).

Soft Skills We Value

 * Takes pleasure in their craft and enjoys building clean, reliable systems.
 * Is excited to be part of a beautiful technical adventure, shaping a platform from the ground up.
 * Can explain complex data flows and architecture clearly to teammates from different backgrounds.
 * Values collaboration and works closely across disciplines.
 * Brings a problem-solving mindset and finds pragmatic solutions in complex situations.
 * Feels ownership over their work and is motivated by contributing to a sustainable future.
 * Is willing to grow within our Software & Data department.

## Description

As a Data Engineer at MegaCharge, your mission is to build the data backbone of our EMS. Every optimization, dashboard and customer insight depends on data that is complete, timely and trustworthy. You make sure it is.

You will work in close partnership with our Software Engineer, our R&D team. You won't need to invent optimization algorithms or build operator interfaces. Instead, you design and run the pipelines, storage and data models that feed them: from device and market data coming in, to clean, well-documented datasets going out.

Your input will be valued at every stage. You will actively influence how our data architecture evolves and collaborate across departments, from hardware and operations to R&D, to make sure every perspective is reflected in a robust, sustainable data platform., * Data Pipelines: Design, build and maintain batch and streaming pipelines that ingest data from chargers, batteries, solar installations, grid and energy market APIs.

 * Time Series Data Platform: Model, store and serve high-volume time series data efficiently for both real-time use and historical analysis.
 * Data Modeling & Schemas: Maintain clean, versioned schemas and data contracts for downstream use by the EMS backend, R&D and dashboards.
 * Data Quality & Reliability: Implement validation, anomaly and gap detection, retries and alerting, so that faulty or missing data is caught early.
 * Monitoring & Observability: Monitor pipeline health, latency and costs. Provide the data layer for monitoring dashboards (e.g. Grafana).
 * Traceability & Governance: Ensure lineage, structured logging and auditability of data flows, in line with our cybersecurity and IAM principles.
 * Cloud Infrastructure: Build and manage our cloud data stack in coordination with the cloud team, with a focus on performance and cost efficiency.
 * Collaboration with R&D: Prepare datasets and feature pipelines for optimization, forecasting and ML models, and support their move into production.
 * Documentation & Testing: Produce clear architecture and data documentation, and maintain code quality through tests and GitLab CI/CD workflows.