Databricks Admin & Data Engineering Lead

Accenture; Nashville (TN); On-site; USD 90,000 - 150,000; Full time

Job summary

Accenture Flex seeks a Data Engineer to design, develop, and maintain data solutions that support data generation, collection, and processing. You will create data pipelines, ensure data quality, and implement ETL to migrate data across systems while leading and mentoring a team across multiple projects.

The role emphasizes collaboration with cross-functional teams, adoption of best practices in data engineering and administration, and ongoing evaluation of emerging technologies to improve data

Qualifications

• Minimum 4 years of work experience.
• Master proficiency in Databricks Administration is required.
• High School Diploma/GED.
• Expert proficiency in Snowflake Platform is recommended.
• Expert proficiency in Data Migrations, Data Engineering, Data Pipelines, and Data Processing is suggested.

Responsibilities

• Design, develop, and maintain data solutions supporting data generation, collection, and processing.
• Create data pipelines and ensure data quality; implement ETL to migrate data across systems.
• Lead and mentor team members; collaborate with multiple teams to meet project goals.
• Troubleshoot complex data issues and implement robust solutions for reliability.
• Evaluate emerging data technologies to improve workflows and efficiency.
• Collaborate with cross-functional teams to align data engineering with organizational goals.

Skills

Team leadership

Education

High School Diploma/GED

Tools

Databricks Administration

Snowflake Platform

Data Migrations

Data Engineering

Data Pipelines

Data Processing

Job description

Accenture Flex seeks a Data Engineer to design, develop, and maintain data solutions that support data generation, collection, and processing. You will create data pipelines, ensure data quality, and implement ETL to migrate data across systems while leading and mentoring a team across multiple projects.

The role emphasizes collaboration with cross-functional teams, adoption of best practices in data engineering and administration, and ongoing evaluation of emerging technologies to improve data