Data Engineering Lead

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

$106K-$221K not verified - source not recorded; timestamp not recorded

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

46% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Engineering Lead Arlington, VA 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,

Read the full description at boards.greenhouse.io. FewerJobs shows a source-linked preview and links to the original posting.