Accenture Flex offers you the flexibility of local fixed-duration project-based work powered by Accenture, a leading global professional services company. Accenture is consistently recognized on FORTUNE's 100 Best Companies to Work For and Diversity Inc's Top 50 Companies For Diversity lists.

As an Accenture Flex employee, you will apply your skills and experience to help drive business transformation for leading organizations and communities. In addition to delivering innovative solutions for Accenture's clients, you will work with a highly skilled, diverse network of people across Accenture businesses who are using the latest emerging technologies to address today's biggest business challenges.

You will receive competitive rewards and access to benefits programs and world-class learning resources. Accenture Flex employees work in their local metro area onsite at the project, significantly reducing and/or eliminating the demands to travel.

Role Overview:

As a Data Engineer, you will be responsible for designing, developing, and maintaining data solutions that support data generation, collection, and processing. Your day-to-day activities will include creating data pipelines, ensuring data quality, and implementing extract, transform and load processes to migrate and deploy data across various systems. You are expected to be a subject matter expert, collaborate and manage the team to perform effectively, take responsibility for team decisions, engage with multiple teams, contribute to key decisions, and provide solutions to problems within your immediate team and across multiple teams.

Responsibilities:

• Master proficiency in Databricks Administration is required. Expert proficiency in Snowflake (Platform) is recommended. Expert proficiency in Data Migrations, Data Engineering, Data Pipelines, and Data Processing is suggested.

• Develop and optimize scalable data architectures to support evolving business needs and data strategies.

• Lead efforts to troubleshoot complex data issues and implement robust solutions to enhance system reliability.

• Collaborate with cross-functional teams to align data engineering efforts with organizational goals and project requirements.

• Support and mentor colleagues by sharing expertise and promoting best practices in data engineering and administration.

• Continuously evaluate emerging technologies and tools to improve data workflows and operational efficiency.