11 дней назад
Data Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
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TL;DR
Data Engineer (AI): Building and optimizing large-scale data pipelines for a core data warehouse and AI projects with an accent on high-volume data ingestion, cloud and on-premise deployment, and close collaboration with Data Scientists. Focus on designing critical pipelines, processing data with Spark, and optimizing advanced data formats and distributed infrastructure.
Location: Ra'anana, Israel
Company
provides AI-led professional and managed cloud services, supporting AWS and Salesforce migrations, implementations, and ongoing management for clients across EMEA and North America.
What you will do
- Ingest large volumes of new data for a core data warehouse and AI projects.
- Examine and analyze data in close collaboration with Data Scientists.
- Design and develop critical, diverse, and large-scale data pipelines and processes.
- Deploy and optimize data solutions across cloud and on-premise environments.
- Work with development, production, and end-user interfaces.
Requirements
- B.Sc. in Computer Science, Engineering, Mathematics, or Statistics is mandatory.
- At least 3 years of experience as a Data Engineer and at least 3 years of Python development experience; Python development experience is mandatory.
- Hands-on experience with Object-Oriented Programming and Spark for large-scale data processing.
- Hands-on experience with dbt and experience building and maintaining data pipelines using tools such as Airflow or Kubeflow.
- Practical experience with Docker and container platforms such as ECS or Kubernetes.
- Understanding of optimization techniques and advanced data formats, including Parquet and Iceberg, as well as Avro, HDF5, and Delta Lake.
- Experience with AWS data services including Athena, Glue, EMR or EMR Serverless, Redshift, and RDS is a significant advantage.
- Experience integrating BI tools such as QuickSight, Tableau, and Power BI.
- Understanding of Machine Learning concepts and processes.
- Initiative, independence, teamwork, self-learning ability, strong analytical skills, and the ability to work under pressure with a high level of responsibility and commitment.
Nice to have
- Practical knowledge of GenAI and prompt engineering solutions.
- Hands-on experience with AWS data services is a significant advantage.
Culture & Benefits
- Learning and personal development supported by experienced leaders.
- Competitive salary and bonus incentives.
- Benefits, flexible hours, and mentoring.
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