ML Engineer [PySpark]

Tech4ces; Eu; À distance; EUR 70 000 - 100 000; Plein temps

Résumé du poste

Tech4ces is seeking a Senior ML Engineer (PySpark) to help increase ML-driven automation in our data analytics landscape. You will design, build, and optimize large-scale data pipelines and data models, exposing insights through advanced visualizations to support actionable decisions.

The role requires strong PySpark, SQL, and DataOps experience, with exposure to AWS, Hive, Airflow, Snowflake, and Tableau. This is a remote position with a 6-month term, extendable, starting asap.

Qualifications

• Demonstratable experience with PySpark and Jupyter Notebooks.
• Experience with AWS, Hive, and Airflow.
• Exposure to Snowflake, Tableau, or similar alternatives.
• Data Modelling literate and proficient in SQL.

Responsabilités

• Design, manage and support the preparation of large, complex data sets.
• Create production-ready big data pipelines.
• Design and implement data models.
• Promote DataOps & MLOps culture.

Connaissances

PySpark

Jupyter Notebooks

SQL

Agile

DataOps

Data Modelling

Snowflake

Tableau

Airflow

Hive

AWS

Outils

Hive

Airflow

Snowflake

Tableau

Description du poste

ML Engineer [PySpark]

Reference : EU170380

• EU
• Remote
• Senior
• 6 months
• Extendable
• asap

A global manufacturing company of apparel, equipment, and accessories is looking for experienced Machine Learning engineers.

Job Description

Increase the process automation powered by ML in the data analytics landscape and implement advanced data visualizations to expose analytical insights driving intuitive actionable decisions.

Responsibilities

• Design, manage and support the preparation of large, complex data sets
• Create production-ready big data pipelines
• Design and implement data models.
• Promote DataOps & MLOps culture

Skills And Qualifications

• Demonstratable experience with PySpark and the use of Jupyter Notebooks.
• Experience with AWS, Hive, and Airflow
• Exposure to Snowflake, Tableau, or similar alternatives
• Data Modelling literate
• Proficiency in SQL
• Well versed with Agile methodology and DataOps