Data Engineer

Accenture Federal Services•Arlington, VA

5h•$103,200 - $196,400

About The Position

Accenture Federal Services is seeking a Data Engineer to build and optimize scalable data pipelines supporting enterprise analytics, reporting, AI, and machine learning initiatives. The role focuses on hands-on data engineering with Google Cloud Platform (GCP), modern data architectures, and cloud-based solutions. The engineer will deliver curated datasets, build ML-ready feature pipelines, and collaborate with data scientists, ML engineers, architects, and business stakeholders.

Requirements

At least 3 years of Data Engineering experience.
Expertise in Python, SQL, and data modeling.
Hands-on experience with GCP services including BigQuery, Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, Cloud Storage (GCS), and Cloud Composer (Airflow).
Experience with ETL/ELT and batch and streaming data pipelines.
Knowledge of Terraform, CI/CD, and data quality best practices.

Nice To Haves

Experience with Vertex AI, Kafka, Dataplex, Datastream, dbt, or Looker.
Experience supporting ML/AI workloads.
Federal Government or regulated industry experience, including FedRAMP, HIPAA, or NIST.
CISSP or CCSP certification.

Responsibilities

Design, build, and maintain batch and streaming data pipelines.
Ingest and transform data from APIs, databases, SaaS applications, and streaming platforms.
Develop ETL/ELT processes using Python, SQL, Apache Beam (Dataflow), Spark (Dataproc), and BigQuery.
Deliver high-quality, curated datasets for analytics, reporting, and machine learning.
Build ML-ready feature pipelines and support AI initiatives.
Implement data quality, testing, monitoring, and governance standards.
Optimize BigQuery performance, data models, and storage structures.
Manage workflow orchestration using Cloud Composer (Airflow).
Support Infrastructure as Code using Terraform and CI/CD deployment processes.
Collaborate with Data Scientists, ML Engineers, Architects, and business stakeholders.