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Machine Learning Engineer
1 month ago
Required Education and Experience
- Bachelor's degree in Computer Science, Information Technology, or related field
- 3+ years of experience in data engineering or related roles, preferably in a cloud environment
- Experience with cloud-based data platforms (e.g., Azure Databricks, AWS EMR)
- Proficiency in programming languages such as Python, SQL, and Scala
- Proficiency with Power BI for data visualization and reporting
- Strong understanding of data modeling, ETL processes, and data warehousing concepts
- Familiarity with big data technologies
- Innovative and adaptable, with a passion for continuous learning and improvement
- Strong communication and collaboration skills, with the ability to work effectively across teams
- Results-oriented and committed to delivering high-quality solutions that meet business needs
- Ethical conduct and commitment to safety in all aspects of work
- Data Pipeline Development: assist in designing, building, and maintaining scalable data pipelines for ingesting, transforming, and storing large volumes of AMI data from various sources; collaborate with data scientists to integrate data pipelines with analytical models and AI processes
- Data Modeling and Architecture: develop and implement optimized data models and architectures for AMI data analytics, ensuring efficiency, scalability, and data integrity; implement best practices for data storage, partitioning, and indexing to optimize performance and facilitate analysis
- Cloud Environment Management: deploy, manage, and optimize data engineering solutions within Azure cloud environments; collaborate with cloud architects and administrators to ensure security, compliance, and cost-effectiveness of cloud infrastructure
- Visualization and Reporting: develop and maintain Power BI dashboards and reports to visualize AMI data insights and support data-driven decision-making; create custom UI/UX applications to enhance data visualization effectiveness
- Data Cataloging and Documentation: catalog and document AMI data sources, datasets, and metadata to facilitate data discovery, lineage, and governance; implement data cataloging best practices to ensure availability and accessibility of AMI data assets
- Collaboration and Support: collaborate with cross-functional teams to understand data requirements and support analytical initiatives; provide technical support and troubleshooting for data-related issues to ensure reliability and availability of data infrastructure