Databricks Admin & Data Engineering Lead

Accenture; Austin (TX); On-site; USD 105,000 - 126,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Paid time off

Job summary

Accenture Flex in Austin seeks a skilled Data Engineer to design, develop, and maintain data solutions supporting data generation, collection, and processing. You will build data pipelines, ensure data quality, and migrate data across systems while mentoring teammates to drive effective performance.

The role requires expertise in Databricks Administration and Snowflake, with a focus on data migrations, engineering, pipelines, and processing.

Qualifications

• Minimum 4 years of work experience.
• Master proficiency in Databricks Administration is required.
• High School Diploma/GED

Responsibilities

• Master proficiency in Databricks Administration is required.
• 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.

Skills

Databricks Administration

Snowflake Platform

Data Migrations

Data Engineering

Data Pipelines

Data Processing

Education

High School Diploma/GED

Job description

Accenture Flex in Austin seeks a skilled Data Engineer to design, develop, and maintain data solutions supporting data generation, collection, and processing. You will build data pipelines, ensure data quality, and migrate data across systems while mentoring teammates to drive effective performance.

The role requires expertise in Databricks Administration and Snowflake, with a focus on data migrations, engineering, pipelines, and processing.