Ai & data engineer
the divisional data & ai engineer will be responsible for designing, developing, and implementing data-driven solutions to support the division's strategic objectives. This role involves working closely with cross-functional teams to leverage data and ai technologies to drive innovation, improve operational efficiency, and enhance decision-making processes (engineering, manufacturing, business).
what you’ll do:
1. data engineering:
* design, develop, and maintain scalable data pipelines and etl processes to ensure the availability and quality of data for analysis and reporting.
* collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs.
* implement data governance and data quality best practices to ensure the integrity and security of data assets.
1. ai & machine learning:
* develop and deploy machine learning models and ai solutions to address business challenges and opportunities.
* work with data scientists to experiment with and implement advanced analytics techniques, including predictive modeling, natural language processing, and computer vision.
* monitor and evaluate the performance of ai models and continuously improve their accuracy and efficiency.
2. collaboration & communication:
* collaborate with it, operations, and business teams to identify and prioritize data and ai initiatives.
* communicate complex technical concepts and insights to non-technical stakeholders in a clear and concise manner.
* provide training and support to team members on data and ai tools and methodologies.
3. innovation & continuous improvement:
* stay up-to-date with the latest trends and advancements in data engineering, ai, and machine learning.
* identify opportunities for process improvements and automation using data and ai technologies.
* contribute to the development of best practices and standards for data and ai engineering within the division.
what is required:
* bachelor's or master's degree in computer science, data science, engineering, or a related field (preferred)
* proven experience in data engineering, machine learning, and ai development.
* proficiency in programming languages such as python, r, or java.
* experience with data processing frameworks (e.g., apache spark, hadoop) and cloud platforms (e.g., azure, aws).
* strong understanding of database systems, data warehousing, and etl processes.
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