Senior Data Engineer (UK REMOTE)

at  Turnitin LLC

100% REMOTE MUST BE UK BASED

At Turnitin, an AI-centric leader in the educational and research sectors, we’ve been innovating and promoting academic integrity for over two decades. We have an established reputation for our advanced solutions, utilized by numerous academic institutions, corporations, and publishers worldwide.
Offering remote work as a default arrangement, we honor individual choices, value diversity, and respect local cultures. However, for those who prefer the office environment, we have multiple locations across the globe including Oakland, Dallas, Pittsburgh, Kyiv (Ukraine), Newcastle (UK), and Utrecht (Netherlands). Our team is diverse, but unified by our commitment to significantly impacting the realm of education.
As a Senior Data Engineer at Turnitin, you will be part of a global team of proactive, supportive, and independent professionals, striving to deliver sophisticated, well-structured AI and data systems. Collaborating closely with different teams within Turnitin, you’ll integrate AI and data science across our broad suite of products, further enriching learning, teaching, and academic integrity.
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.

• 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