Data Engineering Lead

Requirements

• 8 years of experience in data engineering, data pipeline design, and management
• Must meet DoD 8140 requirements
• Bachelor's degree (or 4 years of additional equivalent experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering
• Security Clearance:
• Active TS/SCI clearance
• The pay range for the states of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Washington, Vermont, the District of Columbia, and the city of Cleveland is:
• $116,900 - $234,100 USD
• What We Believe
• Equal Employment Opportunity Statement
• Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and wom

Benefits

Additional Information

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! Job Description The Data Engineer will design, build, and maintain the core client data infrastructure and pipelines necessary to ingest, process, store, and transform data for various consumers. Develop and operate automated, end-to-end data pipelines, create and maintain data models and schemas, and contribute to the overall scalability, reliability, and security of the data platform. Implement data processing frameworks and technologies, design and optimize data storage solutions, and develop data transformation logic to support analytics requirements. Implement data quality checks and validation procedures, establish data lineage tracking mechanisms, and troubleshoot data pipeline issues. Collaborate with data scientists and analysts to understand data requirements, work with security teams to implement data protection measures, and stay current with data engineering technologies and best practices. Document data architecture and pipelines, participate in data governance activities, and contribute to continuous improvement of data engineering processes.

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