Full-Time Senior Data Engineering

Position Description 

• Meet with stakeholders to understand the big picture and asks. 
• Recommend architecture aligned with the goals and objectives of the product/organization. 
• Recommend standard ETL design patterns and best practice. 
• Drive the detail design and architectural discussions as well as customer requirements sessions to support the implementation of code and procedures for our big data product.
• Design and develop proof of concept/prototype to demonstrate architecture feasibility. 
• Collaborate with developers on the team to meet product deliverables. 
• Must have familiarity with data science tech stack. Any one of the  languages :SAS,SPSS code or R-code. 
• Work independently and collaboratively on a multi-disciplined project team in an Agile development environment. 
• Ability to identify and solve for code/design optimization. 
• Learn and integrate with a variety of systems, APIs, and platforms. 
• Interact with a multi-disciplined team to clarify, analyze, and assess requirements. 
• Be actively involved in the design, development, and testing activities in big data applications. 
• Hands-on experience Python and Pyspark, Jupyter Notebooks, Python. 
• Familiarity with Databricks. Azure Databricks is a plus. 
• Familiarity with data cleansing, transformation, and validation. 
• Proven architecture skills on Big Data  projects. 
• Hands-on experience with a code versioning tool such as GitHub, Bitbucket, etc. 
• Hands-on experience building pipelines in GitHub (or Azure Devops,Github, Jenkins, etc.) 
• Hands-on experience with Spark. 
• Strong written and verbal communication skills. 
• Self-motivated and ability to work well in a team. 

Any mix of the following skills is also valuable: 

• Experience with data visualization tools such as Power BI or Tableau. 
• Experience with DEVOPS CI/CD tools and automation processes (e.g., Azure DevOPS, GitHub, BitBucket). 
• Experience with Azure Cloud Services and Azure Data Factory. 
• Azure or AWS Cloud certification preferred. 

Education:

• Bachelor of Science degree from an accredited university 

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)