Overview
On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
Skills
Data Engineering
AI/ML
AI ML
AI
ML
Aws
Azure
SQL
Spark
Python
Bigdata
Databricks
AWS EMR
AWS Glue
Hadoop
Job Details
Please send your resume to pratap (at) tekaccel (dot) com
Data Architect
Location: Corvallis, OR Onsite Role
Long Term Project - Contract & Full Time Options
Job Description:
The data engineering role is a team member that will help enhance and maintain the CSS Business Analytics and Instant Ink Business Intelligence system. You will drive work you're doing to completion with hands-on development responsibilities, and partner with the Data Engineering leaders to implement data engineering pipelines to build solution to help provide trusted and reliable data to customers.
Responsibilities:
- At least 15+ years experience in data engineering , AI ML and Aws/Azure
- Architect, Design and implement distributed data processing pipelines using Spark, Python, SQL and other tools and languages prevalent in the Big Data/Lakehouse ecosystem.
- Experience in AI and ML on AWS/AZURE
- Analyzes design and determines coding, programming, and integration activities required based on general objectives.
- Play the technical lead role representing deliverables from vendor team resources at onsite and offshore locations.
- Lead the technical co-ordination and Business Knowledge transition activities to offshore team.
- Reviews and evaluates designs and project activities for compliance with architecture, security and quality guidelines and standards.
- Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies defects and creates solutions for issues with code and integration into data system architecture.
- Collaborates and communicates with project team regarding project progress and issue resolution.
- Works with the data engineering team for all phases of larger and more-complex development projects and engages with external users on business and technical requirements.
- Collaborates with peers, engineers, data scientists and project team.
- Typically interacts with high-level Individual Contributors, Managers and Program Teams on a daily/weekly basis.