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.

The work you'll do:

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.

Here's what you'll need:

3 to 5+ years of experience with data engineering, data warehousing, and/or big data processing.

Google Cloud Platform (GCP) Data Engineer

Responsibilities

Qualification

Required

Preferred

Company

Accenture Federal Services

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