Google Cloud Platform (GCP) Data Engineer

Accenture Federal Services•Arlington, TX

About The Position

At Accenture Federal Services, our purpose is to make the US federal government stronger and safer, and to improve people's lives. Our 13,000+ employees are dedicated to leveraging technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within the global Accenture network. We are recognized as a Glassdoor Top 100 Best Place to Work, offering a supportive community where you can grow, learn, and thrive through hands-on experience, certifications, and industry training. Contribute to positive, lasting change that advances missions and the government.

Requirements

3 to 5+ years of experience in data engineering, data warehousing, or big data processing.
2+ years of hands-on experience building data pipelines and/or data solutions on Google Cloud Platform (BigQuery, Dataflow, Cloud Composer).
Strong programming skills in Python and advanced proficiency in SQL.
Experience with ETL/ELT concepts and tools.
Active Top Secret (TS) security clearance is required.

Nice To Haves

Google Cloud Professional Data Engineer Certification.
Experience with migrating legacy relational databases (e.g., Oracle, SQL Server) to cloud-native databases (e.g., Cloud SQL, AlloyDB, Spanner).
Familiarity with federal data strategies, RMF, and Impact Level 4/5 (IL4/IL5) security and compliance standards.

Responsibilities

Design, develop, and maintain robust data pipelines and ETL processes for seamless integration, cleansing, harmonization, and transformations in large-scale data processing systems and data lakes/data warehouses using GCP native services (BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub).
Implement performance tuning (partitioning, broadcast joins, caching, shuffle optimization).
Integrate data from multiple sources (databases, APIs, cloud storage, potentially streaming).
Migrate legacy data stores and ETL pipelines to modernized, cloud-native architectures on GCP.
Develop scalable batch and real-time streaming data pipelines using Python, SQL, and Apache Beam.
Implement data governance, data quality checks, and secure data access controls in alignment with strict federal security requirements.
Collaborate with data scientists, cloud infrastructure engineers, and mission stakeholders to optimize data models and query performance.
Design and Implement CI/CD Pipelines: Architect and build robust, automated CI/CD pipelines to streamline the build, test, and deployment processes from development through to production environments.