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Accenture Federal Services

Data Engineer

Accenture Federal Services

. Build, maintain, and optimize batch and streaming data pipelines for analytics and AI workloads .

Posted 10/6/2026full-timeRemote • United StatesMid-LevelSenior💰 $103,200 - $196,400 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and optimizing data pipelines for analytics and AI workloads, with a strong focus on data ingestion, transformation, and quality assurance. Proficient in utilizing cloud technologies and tools for data governance, security, and compliance.

Highest-signal resume keywords
Data Pipeline DevelopmentBigQuery OptimizationDataflow (Apache Beam) ProficiencyGovernance and Compliance StandardsPython and SQL Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Pipeline DevelopmentBigQuery SQLPythonDataflow (Apache Beam)Dataproc (Spark)SQLData ModelingDistributed Data ProcessingCloud Composer (Airflow)Terraform
Soft Skills
CollaborationTechnical LeadershipProblem-SolvingDocumentation
Tools & Technologies
Google Cloud Platform (GCP)Pub/SubGCSCloud MonitoringCloud LoggingDataplex/Data CatalogCI/CD Deployment Pipelines
Industry Keywords
Data EngineeringMachine LearningData GovernanceSecurity FrameworksCompliance Standards

Tech Stack

Tools & technologies
AirflowApacheBigQueryCloudGoogle Cloud PlatformPythonSparkSQLTerraform

About the role

Key responsibilities & impact
  • Build, maintain, and optimize batch and streaming data pipelines for analytics and AI workloads
  • Ingest structured, semi-structured, and unstructured datasets from APIs, databases, SaaS systems, streaming feeds, and file-based sources
  • Transform, clean, enrich, and standardize data using Dataflow (Apache Beam), Dataproc (Spark), BigQuery SQL, and Python
  • Deliver curated datasets into BigQuery for analytics, reporting, and machine learning training
  • Build and maintain ML-ready feature pipelines
  • Implement data quality checks, schema validation, and automated pipeline testing
  • Monitor pipeline health using Cloud Monitoring and Cloud Logging
  • Apply governance, security, and compliance standards including IAM roles, encryption, data masking, and auditing
  • Enforce schema evolution, metadata management, and lineage tracking using Dataplex/Data Catalog
  • Maintain documentation for datasets, transformations, pipeline logic, and operational procedures
  • Write maintainable Python, SQL, Beam, and Spark code
  • Manage ingestion flows using Pub/Sub, GCS, APIs, Datastream, and database connectors
  • Optimize BigQuery tables, partitions, clustering, materialized views, and query performance
  • Implement and maintain DAGs with Cloud Composer (Airflow)
  • Troubleshoot pipeline failures, latency issues, and data quality gaps
  • Participate in code reviews, architectural discussions, and agile sprint ceremonies
  • Collaborate with Data Architects, Data Scientists, ML Engineers, and business stakeholders
  • Develop and maintain Infrastructure as Code using Terraform and CI/CD deployment pipelines

Requirements

What you’ll need
  • Bachelor’s degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or related technical field
  • 3–6+ years of hands-on experience in data engineering or a similar technical field
  • Minimum three years of experience leading technical teams to achieve outcomes
  • Experience developing and implementing technical standards for cloud and on-prem environments
  • Proven experience building production data pipelines on cloud platforms, preferably GCP
  • Hands-on experience with BigQuery, GCS, Dataflow (Apache Beam), Dataproc (Spark), and Pub/Sub
  • Experience preparing ML-ready datasets for model training
  • Strong background in SQL, Python, distributed data processing, and data modeling
  • Experience with governance, security, and compliance frameworks including IAM, encryption, data masking, and auditing
  • Familiarity with Google Cloud Security tools, Google Cloud Monitoring & Logging tools, Google Cloud Networking, and Google Storage services
  • Must have US work authorization that does not now or in the future require visa sponsorship

Benefits

Comp & perks
  • Collaborative and caring community
  • Hands-on experience
  • Certifications
  • Industry training
  • Wide variety of benefits (details provided via employer benefits information)