
Data Engineer and Machine Learning Specialist
1 week ago
We are seeking a highly skilled professional to join our technology team as a data engineering expert. The ideal candidate will have a strong background in software development, machine learning, and financial data.
Key Responsibilities:- Data Pipeline Development: Design and build robust, maintainable software systems to support data pipelines, analytics, and AI applications.
- Collaboration and Tooling: Collaborate with domain experts to scope, build, and iterate on AI-driven tools tailored to business needs.
- Data Ingestion and Transformation: Develop efficient data ingestion, transformation, and validation pipelines using Python, SQL, and modern libraries.
- AI Integration: Integrate large language models (LLMs) and generative AI APIs into internal tooling.
- User Interface and Visualization: Create clean, intuitive user interfaces and data visualizations with libraries like Plotly and Dash.
- Database Performance: Optimize database access and performance for large structured and semi-structured datasets.
- Scalability and Security: Ensure tools are scalable, secure, and aligned with end-user workflows and UX needs.
- Project Lifecycle: Take projects from concept to production, including testing, documentation, deployment, and iteration.
- Programming Skills: Strong programming skills in Python, with exposure to software engineering best practices.
- SQL and Database Knowledge: Proficiency with SQL and relational databases.
- Data Pipeline Experience: Experience working with data pipelines, ETL workflows, and data wrangling techniques.
- Machine Learning Frameworks: Familiarity with ML frameworks and data libraries.
- Generative AI Experience: Exposure to generative AI or LLM APIs and frameworks.
- Fundamental Concepts: Understanding of fundamental machine learning and data science concepts.
- Communication Skills: Strong written and verbal communication skills.
- User-Focused Mindset: User-focused mindset: you care about who's using your tools and how to make them intuitive, reliable, and useful.
- Team-Oriented: Team-oriented: you work well with others, ask great questions, and contribute to a collaborative culture.
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