Data Engineer

🔥 3 minutes ago

🏛️ District of Columbia, Washington – Remote

🏛️ District of Columbia – Remote ☕ Washington – Remote

💵 $103.2k - $196.4k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 0%

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Accenture Federal Services

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2017

💼 Consulting

🎖️ Defense

📦 Logistics

Consulting • Defense • Logistics

Accenture Federal Services is a division of Accenture that focuses on delivering technology and consulting services to the U. S. federal government. With capabilities in cloud, cybersecurity, data and artificial intelligence, digital engineering, and emerging technologies, Accenture Federal Services supports federal agencies in achieving mission-critical outcomes through innovation and technological advancement. The company emphasizes building secure, scalable solutions, enhancing decision-making with data-driven insights, and transforming digital infrastructures to meet complex governmental needs. By leveraging advanced R&D and human-centered design, they aim to improve the performance and resilience of government operations.

📋 Description

• 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 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 policies, metadata management, and lineage tracking using Dataplex/Data Catalog • Maintain documentation for datasets, transformations, pipeline logic, and operational procedures • Write 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

• 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

• Collaborative and caring community • Hands-on experience • Certifications • Industry training • Equal employment opportunity • Reasonable accommodations for disabilities or religious observances