Google Cloud Platform (GCP) Data Engineer

accenturefederalservices; United States; Remote; USD 120,000 - 190,000; Full time

Benefits offered by this job

Federal benefits package

Job summary

Accenture Federal Services is seeking a data engineer to design and build secure, cloud-native data architectures and pipelines on Google Cloud Platform for federal missions. You will modernize legacy data landscapes to enable advanced analytics and data-driven decision-making across critical programs.

The role emphasizes developing scalable batch and real-time streaming pipelines, implementing governance and secure access, and collaborating with mission stakeholders to refine data models and

Qualifications

• 3–5+ years in data engineering, data warehousing, or big data processing.
• Hands-on GCP experience building data pipelines with BigQuery, Dataflow, or Cloud Composer.
• Strong programming in Python and advanced SQL proficiency.
• Solid grasp of ETL/ELT concepts and tooling.
• Active Top Secret or Interim TS security clearance.

Responsibilities

• Design, develop, and maintain data pipelines and ETL/ELT processes that integrate, cleanse, harmonize, and transform data across large-scale data lakes and warehouses using BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub.
• Apply performance tuning techniques such as partitioning, broadcast joins, caching, and shuffle optimization.
• Integrate data from multiple sources including relational databases, APIs, cloud storage, and streaming systems.
• Migrate legacy data stores and ETL pipelines to modernized, cloud-native architectures on GCP.
• Develop scalable batch and real-time streaming pipelines using Python, SQL, and Apache Beam.
• Implement data governance, data quality checks, and secure access controls aligned with federal security requirements.
• Collaborate with data scientists, infrastructure engineers, and mission stakeholders to refine data models and query performance.
• Architect and maintain CI/CD pipelines that automate build, test, and deployment from development through production.

Skills

Python

SQL

BigQuery

Dataflow

Dataproc

Pub/Sub

Cloud Composer

ETL/ELT

CI/CD

Data pipelines

Tools

Python tooling

Job description

Role overview

This role focuses on designing and building secure, cloud-native data architectures and pipelines on Google Cloud Platform to support strategic data and workload migrations for federal missions. The engineer modernizes legacy data landscapes to enable advanced analytics and data-driven decision-making across critical programs.

Responsibilities

• Design, develop, and maintain robust data pipelines and ETL/ELT processes that integrate, cleanse, harmonize, and transform data across large-scale data lakes and warehouses using BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub.


• Apply performance tuning techniques such as partitioning, broadcast joins, caching, and shuffle optimization.


• Integrate data from multiple sources including relational databases, APIs, cloud storage, and streaming systems.


• Migrate legacy data stores and ETL pipelines to modernized, cloud-native architectures on GCP.


• Develop scalable batch and real-time streaming pipelines using Python, SQL, and Apache Beam.


• Implement data governance, data quality checks, and secure access controls aligned with federal security requirements.


• Collaborate with data scientists, infrastructure engineers, and mission stakeholders to refine data models and query performance.


• Architect and maintain CI/CD pipelines that automate build, test, and deployment from development through production.

Requirements

• 3 to 5+ years of experience in data engineering, data warehousing, or big data processing.


• 2+ years of hands-on GCP experience building data pipelines and solutions with services such as BigQuery, Dataflow, or Cloud Composer.


• Strong programming in Python and advanced SQL proficiency.


• Solid grasp of ETL/ELT concepts and tooling.


• Active Top Secret or Interim TS security clearance.

Nice to have

• Google Cloud Professional Data Engineer certification.


• Experience migrating legacy relational databases (Oracle, SQL Server) to cloud-native options like Cloud SQL, AlloyDB, or Spanner.


• Familiarity with federal data strategies, the Risk Management Framework, and Impact Level 4/5 (IL4/IL5) compliance.

Benefits and work setup

• U.S.-based federal services role with disclosed compensation ranges tied to specific state labor markets; benefits package referenced by the employer.