Google Cloud Platform (GCP) Data Engineer

Accenture Federal Services•Arlington, VA

1d•$100,200 - $203,400

About The Position

Accenture Federal Services is looking for a specialized Google Cloud Platform (GCP) Data Engineer to support strategic data and workload migrations. In this role, you will be responsible for designing and building robust, secure data architectures and pipelines on GCP. You will help modernize federal data landscapes, enabling advanced analytics and data-driven decision-making for critical mission objectives.

Requirements

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