Key skills
AirflowApacheETLNumpyPandasPythonPyTorchScikit-LearnSparkTensorflowMachine LearningMLTensorFlowscikit-learnNumPyMLOpsELTData EngineeringApache Spark
About this role
Role Overview
- Design and optimize data pipelines (ETL/ELT);
- Ensure data quality, integrity and availability;
- Lead Data Engineering and MLOps strategies;
- Support training, inference, and monitoring of ML models;
- Mentor team members and support technical decision-making.
Requirements
- Strong experience with machine learning and end-to-end analytical models;
- Extensive background in Data Engineering and tools such as Apache Spark, Airflow, or similar;
- Proficient in Python, Pandas, NumPy, and ML libraries such as Scikit-learn, TensorFlow, or PyTorch;
- Experience with MLOps practices (model versioning, monitoring, and retraining);
- Familiarity with Big Data ecosystems, Data Lakes, and Data Warehouses.
Tech Stack
- Airflow
- Apache
- ETL
- Numpy
- Pandas
- Python
- PyTorch
- Scikit-Learn
- Spark
- Tensorflow