Software Engineer

Requisition Number: 93989

Job Duties:

1. Build the infrastructure required for optimal extraction, transformation, and loading of various types of data coming from a myriad of sources
2. Design, create and maintain optimal data pipelines
3. Identify, design, and implement process improvements, automation opportunities, optimizations, and redesigning of infrastructure for scalability
4. Design data storage solutions likes lakes and warehouses
5. Work with stakeholders to assist with data related technical issues and support their data infrastructure needs
6. Utilize and apply data technologies including Azure SQL Database, Azure SQL Data Warehouse and Azure Data Factory, and other big data technologies, such as, Azure Data Lake and Azure

Salary: Available upon request

Work Schedule: 40 hours/week

Job Requirements:

Education Requirements: Master's degree in Management Information Systems, Computer Science, or closely related.

Experience Requirements: 24 months of fulltime, part-time, or combination of fulltime and part-time experience in job offered, Graduate Assistant, Risk Analyst I, Programmer Analyst, or closely related. Employer will accept part-time experience if it is at least 20 hours per week.

Special skills requirements:

1. Deep understanding of relational databases and ACID properties, and No-SQL document, columnar, key-value, graph databases and BASE properties, to be able to suggest and build solutions to clients depending on the nature of requirement
2. Experience with SQL, Python, PySpark, Pandas, NumPy, Matplotlib and Seaborn to extract, transform, load, visualize, and analyze data
3. Experience and knowledge of the following:
   1. Designing scalable OLTP systems to handle execution of number of transactions occurring concurrently on data at scale
   2. Designing scalable OLAP systems to enable reporting, data discovery, complex analytical calculations, and multi-dimensional analysis of data at scale
   3. Reporting tools like Tableau to enable business intelligence
   4. Kimball's Data warehouse approach along with, star and snowflake schemas to enable quick development of query performant warehouses
   5. Distributed data stores like HDFS, and principles of consistency, availability, and partition tolerance, to be able to suggest and build solutions for clients depending on the nature of requirement
   6. Optimization techniques like indexing and data sharding to enable highly optimized and performant data consumption
   7. Hadoop Map Reduce to build ETL solutions involving batch big data processing
   8. Spark RDDs and dataframes to build ETL solutions involving batch and real-time big data processing

Qualified applicants send cover letter and resumes to: Insight Direct USA, Inc., Susan Triggs, Insight Corporate Paralegal, [email protected], ref job#PR01. EOE.

Insight is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.

Posting Notes: Raleigh || North Carolina (US-NC) || United States (US) || Sales/Business Development || None || US - Raleigh, NC ||

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