Website:
cryscol.com
Job details:
Company Description Cryscol Solutions leverages advanced digital technologies to automate business processes and help enterprises accelerate growth while achieving sustainable cost optimization. As a dedicated technology partner, the company advises clients on digital strategy and modern architectures that support long-term innovation. Cryscol Solutions designs and builds robust software and digital products tailored to complex business needs across industries. Team members collaborate closely with clients to deliver scalable, secure, and high-performance solutions that create measurable business value.
Role Description This is a full-time remote role for an AI Data Engineer (MySQL \ Vector DB) at Cryscol Solutions. The AI Data Engineer will design, implement, and maintain data pipelines that support AI and analytics workloads, with a focus on MySQL and vector databases. Daily responsibilities include building and optimizing ETL processes, modeling data for both transactional and analytical use cases, and configuring vector search capabilities to support AI-driven features. The role involves collaborating with data scientists, ML engineers, and application developers to ensure data architectures are scalable, reliable, and secure. The AI Data Engineer will also monitor data quality, troubleshoot performance issues, and contribute to best practices, documentation, and automation of data workflows.
Qualifications
- Strong data engineering skills, including experience with Data Engineering workflows and Data Warehousing concepts.
- Proficiency in Data Modeling and designing schemas optimized for both MySQL and vector databases.
- Hands-on experience building and managing Extract Transform Load (ETL) processes and data pipelines.
- Ability to perform Data Analytics to validate datasets, support AI experiments, and inform data architecture decisions.
- Practical experience with MySQL (schema design, indexing, performance tuning, query optimization).
- Experience with vector databases (e.g., Pinecone, Weaviate, Qdrant, Milvus, or similar) and integrating them into AI or retrieval-augmented applications.
- Proficiency in at least one programming language commonly used for data engineering (such as Python) and experience with SQL at an advanced level.
- Familiarity with cloud platforms (such as AWS, Azure, or GCP) and modern data stack tools (e.g., orchestration frameworks, DBT, or similar) is preferred.
- Understanding of data security, governance, and best practices for handling sensitive and large-scale datasets.
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.
- Strong problem-solving, communication, and collaboration skills, with the ability to work effectively in a fully remote, distributed team.
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