Data Engineer
Role Overview
Full-time Data Engineer role supporting AI-driven solutions and cloud-based data integration with Microsoft Azure.
The role involves close collaboration with software engineers and AI teams to ensure reliable data flows for AI models.
Key Skills for This Role
Full Job Posting
Role overview
Full-time Data Engineer role supporting AI-driven solutions and cloud-based data integration with Microsoft Azure.
The role involves close collaboration with software engineers and AI teams to ensure reliable data flows for AI models.
Key responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes for AI-driven projects.
- Build and optimize Azure data infrastructure for efficient data management, processing, and storage.
- Collaborate with AI engineers to prepare and manage data for machine learning models and AI solutions.
- Ensure pipelines are secure, reliable, and meet performance standards; monitor and troubleshoot performance.
- Implement data governance policies and ensure compliance with data security standards.
Required qualifications
- At least 5 years of professional Data Engineer experience; complex AI or machine learning data pipelines are preferred.
- Strong SQL and experience with PostgreSQL, SQL Server, and MongoDB.
- Hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.
- Experience with data integration tools and ETL frameworks such as Apache Airflow.
- Proficiency in Python or another language used for data manipulation; strong data warehousing knowledge.
- Experience developing and maintaining data pipelines for AI or machine learning workflows.
- Strong problem-solving and analytical skills; bachelor's degree in Computer Science, Engineering, or a related field.
- Good written and spoken English communication skills.
Desirable qualifications
- Familiarity with machine learning models and data preprocessing techniques for AI solutions is desirable.
- Knowledge of Docker and Kubernetes for data pipeline deployment is desirable.
Work location
- Work location is in person.
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