What are the responsibilities and job description for the AI Data Engineer position at Flexjet?
Position Summary
Flexjet is seeking a detail-oriented AI Data Engineer to build and maintain data infrastructure that powers machine learning and AI systems. In this role, you will work closely with data scientists, ML engineers, and software teams to ensure high-quality, reliable, and scalable data pipelines for AI applications.
Duties & Responsibilities
Flexjet is seeking a detail-oriented AI Data Engineer to build and maintain data infrastructure that powers machine learning and AI systems. In this role, you will work closely with data scientists, ML engineers, and software teams to ensure high-quality, reliable, and scalable data pipelines for AI applications.
Duties & Responsibilities
- Design, build, and maintain data pipelines for AI and machine learning workflows
- Collect, clean, and preprocess structured and unstructured data
- Develop and manage datasets for model training, validation, and inference
- Collaborate with ML engineers and data scientists to support model development
- Ensure data quality, integrity, and availability across systems
- Optimize data storage and retrieval for performance and scalability
- Implement data governance, security, and compliance best practices
- Monitor and troubleshoot data pipeline issues
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field (or equivalent experience)
- Strong programming skills in Python and/or SQL
- Understanding of data engineering concepts (ETL/ELT, data modeling, data warehousing)
- Familiarity with machine learning workflows and data requirements
- Experience with data processing tools (e.g., Pandas, Spark)
- Knowledge of relational and non-relational databases
- Basic understanding of cloud platforms (AWS, Azure, or Google Cloud)
- Experience supporting machine learning or AI projects
- Familiarity with big data technologies (e.g., Apache Spark, Kafka, Hadoop)
- Experience with data pipeline orchestration tools (e.g., Airflow, Prefect)
- Knowledge of MLOps practices and tools
- Experience working with unstructured data (text, images, etc.)
- Understanding of data governance and privacy standards
- Strong analytical and problem-solving skills
- Attention to detail and data quality
- Ability to work with cross-functional teams
- Good communication skills
- Ability to manage multiple data workflows