Data Engineer

1. Extensive knowledge of data principles, patterns, processes, and practices
2. Any experience defining evolutionary data solutions and underlying technologies
3. Experience with SQL database design, data modeling
4. Analyze and organize raw data
5. Build data systems and pipelines
6. Evaluate business needs and objectives
7. Interpret trends and patterns
8. Conduct complex data analysis and report on results
9. Demonstrated written and oral communication skills
10. Basic understanding of network and data security architecture
11. Strong knowledge of industry trends
12. Knowledge in a minimum of two of the following technical disciplines: data warehousing, data management, analytics development, data science, application programming interfaces (APIs), data integration, cloud, servers and storage, and database management
13. Experience building cost effective and performance driven solutions using elastic architectures in Microsoft Azure leveraging Cosmos, Azure Data Factory and Databricks Platforms.
14. Experience with SQL and NoSQL applications on Big Data Platforms

• Any experience with operational data science, machine learning or artificial intelligence solutions
• Any experience with data science solutions or platforms
• Data engineering certification (e.g IBM Certified Data Engineer) is a plus

• Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms
• Define high-level migration plans to address the gaps between the current and future state
• Present opportunities with cost/benefit analysis to leadership to shape sound architectural decisions
• Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement
• Promote the reuse of data assets, including the management of the data catalog for reference

Originally posted on Himalayas