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# Data Engineer

- **Company:** Accenture
- **Location:** Tampa, FL, United States
- **Salary:** $114,300.0 - $135,100.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Cloud Computing, Cloud Engineering, Profiling, Code Review, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Visualization, Database Design, Digital Assets, Python (Programming Language), Machine Learning, Scrum Methodology, SQL Databases, Data Streaming, Google Cloud, Data Ingestion, Data Pipelines
- **Published:** September 4, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3377325453&tx=KL5757FFI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Experience with any combination of the following:
 * Skilled in SQL, Python, ETL, data pipelines, and database design.
 * Experienced in building scalable data solutions, dashboards, and automated reporting workflows.
 * Strong background in business metrics, supply chain analytics, and data visualization.

Clearance

 * An active TS/SCI clearance is required

## Description

AFS is searching for a Data Engineer to support the design, development, and maintenance of data pipelines, data models, and analytics platforms. This role is ideal for individuals who are beginning their data engineering career and eager to work with modern cloud, ETL, and automation technologies in a collaborative environment., * Data pipeline development, build, test, and maintain scalable data ingestion and transformation pipelines.

 * Support ETL/ELT activities to move data from source systems to analytics environments.
 * Ensure data workflows are reliable, monitored, and well-documented.
 * Data Modeling & Warehousing to assist in designing and maintaining structured datasets for analytics, reporting, and machine learning use cases.
 * Help define data models, schemas, and metadata within governed data environments.
 * Data Quality & Governance to perform routine data validation, profiling, and quality checks.
 * Collaborate with senior engineers to implement data governance and security best practices.
 * Contribute to documentation of data flows, lineage, and standards.
 * Cloud & Platform Support work with cloud platforms (Azure, AWS, GCP depending on project) to deploy data assets.
 * Support configuration, optimization, and maintenance of compute and storage resources.
 * Collaboration & Delivery to partner with analysts, data scientists, and product teams to understand data requirements.
 * Participate in Agile ceremonies, sprint planning, and code reviews.
 * Drive continuous learning and contribute to improving engineering processes.


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