Senior Data Engineer

Senior Data Engineer in the Engineering team:

Join us in:

• Building and optimizing data architectures to handle large-scale data from various sources, including cloud and on-premise systems.


• Architecting scalable ETL and data workflows to support advanced analytics and machine learning models.


• 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.

Youll 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