Job Description
Your role as a Senior Data Engineer entails a range of responsibilities, necessitating a balanced skillset:
- AI Data Engineering: Design, build, operate and deploy real-time data pipelines at scale using AI techniques and best practices. Support Turnitin's AI R&D efforts by applying advanced data warehousing, data science, and data engineering technologies. Aim for automation to enable a faster time-to-market and better reusability of new AI initiatives.
- Collaboration: Work in tandem with the AI R&D teams and the Data Platform Team to collect, create, curate and maintain high-quality AI datasets. Ensure alignment of data architecture and data models across different products and platforms.
- Innovation: Unearth insights from Turnitin's rich data resources through innovative research and development.
- Hands-on Involvement: Engage in data engineering and data science tasks as required to support the team and the projects. Conduct and own external data collection efforts - including state of the art prompt engineering techniques - to support the construction of state of the art AI models.
- Communication: Foster clear communication within the team and the organization, and ensure understanding of the company's vision and mission.
- Continuous Learning: Keep abreast of new tools and development strategies, bringing innovative recommendations to leadership.
Qualifications
- At least 4 years of experience in data engineering, ideally focused on enabling and accelerating AI R&D.
- Strong proficiency in Python, Java, and SQL.
- Proficiency with Redshift, Hadoop, Elasticsearch, and cloud platforms (AWS, Azure, GCP).
- Familiarity interacting with AI frameworks including PyTorch and TensorFlow and AI libraries such as Huggingface and Scikit-Learn.
- Experience with Large Language Models (LLMs) and LLM APIs.
- Strong problem-solving, analytical, and communication skills, along with the ability to thrive in a fast-paced, collaborative environment.
Desired Qualifications
- 6+ years of experience in data engineering with a focus on AI and machine learning projects.
- Experience in a technical leadership role.
- Familiarity with natural language processing (NLP) techniques and tools.
- Experience in the education or education technology sectors.
- Experience with data visualization and data communications.
Characteristics for Success
- As a Senior Data Engineer, you should possess:
- A passion for creatively solving complex data problems.
- The ability to work collaboratively and cross-functionally.
- A continuous learning mindset, always striving to improve your skills and knowledge.
- A proven track record of delivering results and ensuring a high level of quality.
- Strong written and verbal communication skills.
- Curiosity about the problems at hand, the field at large, and the best solutions.
- Strong system-level problem-solving skills.
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