Python & ETL Developer - 6519350

Accenture•Charlotte, NC

6d•Onsite

About The Position

Accenture Flex is hiring a Python ETL Developer for fixed-duration, project-based work. The role works closely with business representatives, data owners, end users, application designers, and data architects to model current and new data. It involves understanding business requirements, designing data models, and ensuring data integrity and usability across systems. The developer is expected to serve as a subject matter expert, collaborate with and guide a team, contribute to decisions, and solve problems within and across teams. The position requires 80% onsite client work and client-mandated time away five days per quarter. Accenture Flex employees work in their local metro area onsite at the project, reducing or eliminating travel demands.

Requirements

At least 5 years of IT work experience.
Experience in Python, SQL, and ETL development.
Advanced proficiency in Python programming.
Associate degree.
The role requires 80% onsite client work and client-mandated time away five days per quarter.

Nice To Haves

Advanced proficiency in ETL development.
Advanced proficiency in Oracle SQL Developer, data warehouse tools, and the Pandas Python library.
Good communication and leadership skills.
Experience with the PANDA framework.
Banking and finance domain knowledge and experience.

Responsibilities

Work with business representatives, data owners, end users, application designers, and data architects to model current and new data.
Understand business requirements and design data models that support them.
Ensure data integrity and usability across systems.
Collaborate with and manage the team to support effective performance; take responsibility for team decisions and contribute to key decisions.
Engage with multiple teams and provide solutions to problems within the immediate team and across teams.
Develop and refine data models aligned with business strategies and technical requirements.
Analyze complex data structures and provide insights to improve data quality and accessibility.
Support and guide less experienced colleagues by sharing expertise and best practices.
Collaborate with cross-functional teams to ensure seamless integration of data solutions.
Contribute to continuous improvement of data modeling standards and methodologies.