Data Engineer

Data Engineer

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Responsibilities include contributing to the evolution of our data infrastructure and artificial intelligence initiatives.

Responsibilities:

Technical Expertise:

Design and implement a scalable, secure, and efficient data platform to support large-scale data processing, storage, and access for AI applications.

Select and implement appropriate tools and technologies for data ingestion, transformation, storage, and retrieval for AI projects.

Develop and maintain data pipelines for efficient movement and processing of data for AI development and training.

Oversee data quality checks and establish data governance practices to ensure data integrity.

Collaborate with data scientists to understand AI requirements and translate them into technical solutions.

Stay up-to-date on the latest advancements in AI, machine learning, and data engineering technologies.

Communication and Collaboration:

Effectively communicate complex technical concepts to both technical and non-technical audiences.

Document processes, and best practices for knowledge transfer.

Qualifications:

Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field (Bachelor's degree with extensive experience may be considered).

5+ years of experience in data engineering or a related field.

Strong understanding of machine learning pipelines and experience with AI frameworks (TensorFlow, PyTorch, etc.) is a plus.

Extensive experience with big data technologies (Hadoop, Spark, Kafka) and cloud platforms (AWS, Azure, GCP) is essential.

Expertise in SQL and scripting languages (Python, Bash) is required.

Excellent understanding of data modeling principles, data governance, and data security best practices.

Strong communication, collaboration, problem-solving, and leadership skills.