Overview
On Site
DOE
Contract - W2
Skills
Analytical Skill
IWMS
Analytics
Software Design
Shell
Data Processing
Scripting
Decision-making
Data Quality
Continuous Integration
Apache Maven
Jenkins
Ansible
Docker
Continuous Delivery
Computer Science
Data Engineering
Extract
Transform
Load
Informatica
Snap Logic
Snow Flake Schema
Unix
Linux
Operating Systems
Shell Scripting
Python
PL/SQL
Stored Procedures
Data Analysis
Amazon Web Services
Communication
Management
Collaboration
Amazon Lambda
DevOps
Finance
Agile
Kanban
Scrum
Job Details
Job Summary The Data Engineer will play a key role in designing, building, and maintaining operational and analytical capabilities within the organization. As part of the IWMS Analytics and Insights team, this role supports the growth of data infrastructure and contributes to solution design, data analysis, and production rollout activities using Snowflake and AWS technologies. Key Responsibilities Design and implement scalable data solutions using Snowflake and AWS. Participate in solution design, data analysis, and production rollout activities. Develop and maintain ETL processes using tools such as Informatica and SnapLogic. Write and maintain Unix/Linux shell scripts for automation and data processing. Develop Python scripts for data transformation and analysis. Create and optimize Oracle PL/SQL stored procedures. Perform data analysis to support business insights and decision-making. Collaborate with cross-functional teams to ensure data quality and consistency. Contribute to CI/CD pipeline setup and automation using tools like Maven, Jenkins, Stash, Ansible, and Docker. Work within Agile methodologies including Kanban and SCRUM. Support system automation and continuous delivery initiatives. Required Qualifications Bachelors or Masters degree in Computer Science, Engineering, or a related field. Minimum of 8 years of experience in software or data engineering. Hands-on experience with ETL tools (Informatica, SnapLogic) and Snowflake. Proficiency in Unix/Linux operating systems and shell scripting. 34 years of recent experience in Python development. Strong experience with Oracle PL/SQL and stored procedure development. Proven data analysis skills and ability to work with large datasets. Experience working with AWS services. Excellent interpersonal and communication skills. Ability to work in a fast-paced environment and manage ambiguity. Strong collaboration skills across multiple teams. Preferred Qualifications Experience with containerization and deployment pipelines. Familiarity with AWS Lambda and other serverless technologies. Exposure to DevOps practices and tools. Experience in the financial industry. Knowledge of Agile methodologies (Kanban, SCRUM). Education: Bachelors Degree
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.