Databricks Admin Lead: Data Pipelines & Migrations

Accenture; Arlington (VA); On-site; USD 51,000 - 61,000; Full time

Benefits offered by this job

Medical, dental, vision

Long-term disability coverage

401(k) plan

Paid time off

Job summary

Accenture is seeking a Data Engineer to design, develop, and maintain data solutions that support data generation, collection, and processing across systems. You will work to ensure data quality and implement ETL processes to migrate data across platforms.

You will lead data pipelines, collaborate with cross-functional teams, and mentor colleagues while exploring emerging technologies to improve data workflows and reduce operational risk.

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

Data Migrations

Data Engineering

Data Pipelines

Data Processing

Snowflake Platform

Education

High School Diploma/GED

Tools

Snowflake Platform

Job description

Accenture is seeking a Data Engineer to design, develop, and maintain data solutions that support data generation, collection, and processing across systems. You will work to ensure data quality and implement ETL processes to migrate data across platforms.

You will lead data pipelines, collaborate with cross-functional teams, and mentor colleagues while exploring emerging technologies to improve data workflows and reduce operational risk.