About the Role
Our client is seeking a highly experienced Senior AI Data Engineer to join their fully remote team. This role is critical for building and managing the robust data infrastructure required to power our client's advanced artificial intelligence and machine learning initiatives. You will be responsible for designing, developing, and optimizing scalable data pipelines, ensuring the availability, quality, and accessibility of data for AI model training and deployment. As a remote-first organization, we offer a flexible and collaborative work environment where your contributions are valued. The ideal candidate will have a strong background in data engineering, big data technologies, and a solid understanding of AI/ML principles. You will work closely with data scientists, ML engineers, and other stakeholders to deliver high-performance data solutions. This is an excellent opportunity to work with cutting-edge technologies and make a significant impact on the company's AI strategy. We foster a culture of continuous learning and innovation, supporting your professional growth in a dynamic remote setting.
Key Responsibilities
- Design, build, and maintain scalable and efficient data pipelines for AI/ML workloads.
- Develop processes for data ingestion, transformation, cleansing, and aggregation from various sources.
- Implement and manage data warehousing and data lake solutions.
- Optimize data storage, retrieval, and processing for performance and cost-efficiency.
- Ensure data quality, integrity, and security across all data systems.
- Collaborate with data scientists and ML engineers to understand data requirements and provide necessary datasets.
- Implement data governance policies and best practices.
- Monitor data infrastructure performance and troubleshoot data-related issues.
- Explore and implement new data technologies and tools to enhance data capabilities.
- Document data architectures, pipelines, and processes.
Requirements
- Master's degree or equivalent experience in Computer Science, Engineering, or a related quantitative field.
- 5+ years of experience in data engineering, with a focus on big data and AI/ML pipelines.
- Strong proficiency in SQL and NoSQL databases.
- Experience with distributed data processing frameworks like Apache Spark, Hadoop, or Flink.
- Proficiency in programming languages such as Python, Scala, or Java.
- Hands-on experience with cloud data services (e.g., AWS S3, Redshift, Glue; Azure Data Lake, Synapse; GCP BigQuery, Dataflow).
- Familiarity with data warehousing concepts and ETL/ELT processes.
- Understanding of AI/ML model development lifecycle and data requirements.
- Experience with data orchestration tools (e.g., Airflow, Prefect).
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills for a remote environment.
- Experience relevant to the challenges faced by data teams in Kimberley is a plus.
Benefits
- Competitive salary and performance bonuses.
- Comprehensive health, dental, and vision insurance.
- Generous paid time off and holidays.
- Professional development opportunities, including access to training and conferences.
- Opportunity to work with large-scale datasets and cutting-edge AI technologies.
- A supportive and collaborative remote work culture.
- Stock options plan.
- Retirement savings plan with company match.
- Home office stipend to support your remote setup.