Senior Data Engineer

As a Senior Data Engineer in the Engineering team:

Data engineering team builds the robust pipelines that feed the analytics driving the renewable energy sector, enabling real-time monitoring, forecasting, predictive maintenance, and grid optimization for solar, wind, and other sources, ensuring efficiency, reliability, and effective integration into smart grids by managing massive data flows from IoT devices, PLC systems and smart meters. In essence, data engineers create the "data highways" that allow data scientists and AI to turn raw energy data into actionable intelligence, making renewable energy systems smarter, more efficient, and more reliable for a sustainable future

Join us in:

• Building and optimizing data architectures to handle large-scale data from various sources IoT, PLC, SCADA including cloud and on-premise systems.
• Architecting scalable ETL and data workflows to support advanced analytics and machine learning models in Renewable domains
• Collaborating with cross-functional teams to deliver end-to-end data solutions that drive business insights.
• Owning and leading projects that focus on data platform modernization, ensuring high performance, security, and scalability.
• Working on complex data engineering challenges that push the boundaries of cloud data infrastructure.

You'll have:

• A Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 5+ years of experience designing and implementing large-scale data platforms, with at least 2 years of experience leading or mentoring data engineers.
• Hands-on experience with Python (Pandas, Polars) and modern big data tools such as Databricks (Spark), Flink, or Kafka.
• Strong understanding of data pipeline development, ETL frameworks, and data lakes/warehouses.
• Extensive experience with cloud data platforms such as AWS (S3, Redshift, Lambda, Glue), GCP (BigQuery, Dataflow, Dataproc), or Snowflake.
• Familiarity with workflow orchestration tools like Airflow or Prefect.
• Proven ability to lead data engineering teams and mentor junior engineers.

It would be great if you have:

• Experience working with IoT or real-time streaming data.
• Knowledge of data governance frameworks and best practices.
• Exposure to MLOps workflows and integrating data with machine learning models.
• Experience in the energy or manufacturing sector or familiarity with time-series data.
• A strong understanding of data warehousing concepts, including Kimball model design.
• A deep understanding of data security and compliance requirements, particularly in cloud environments.

**A PLUS if you provide the link to your GitHub Website