Data Engineer

Accenture Federal Services•San Antonio, TX

14d•$106,300 - $206,200•Onsite

About The Position

Accenture Federal Services is seeking a Data Engineer to join their team and support their client in the San Antonio, TX area. This role is situated at the intersection of development and operations, focusing on creating CI/CD pipelines, managing cloud environments, and implementing Infrastructure as Code to ensure systems are scalable, secure, and resilient. The company emphasizes its commitment to helping the US federal government, fostering a collaborative and caring community, and empowering employees to grow and thrive. They aim to drive positive, lasting change that moves missions and the government forward.

Requirements

3 years of experience in CI/CD pipeline development and automation
3 years of experience with cloud infrastructure management and monitoring
3 years of experience with Infrastructure as Code and configuration management
3 years of experience with containerization and automated testing
Must have an active Secret clearance; TS/SCI preferred

Nice To Haves

Experience with troubleshooting and continuous process improvement
Knowledge of tuning JVM/GC, YARN, tablet servers, or NiFi performance—aligned with the types of stability and modernization work reflected in internal AFS/Recro big-data engagements
Experience supporting cyber operations or data engineering work in environments using Accumulo, NiFi, and Spark pipelines
Hands-on experience with distributed data platforms including Hadoop and HDFS
Practical experience designing, maintaining, or troubleshooting data ingestion flows using Apache NiFi
Experience building or optimizing Spark-based data processing jobs (PySpark, Scala, or Java)
Familiarity with Accumulo as a high-ingest, low-latency data store, including integration patterns, bulk loading, or iterator development

Responsibilities

Building, automating, and optimizing the infrastructure and processes that enable rapid, reliable software delivery
Working closely with developers to integrate automation, improve deployment workflows, and monitor application performance to maintain high availability across environments
Fostering a culture of collaboration, continuous improvement, and shared ownership across engineering teams
Proactively identifying bottlenecks, recommending architectural enhancements, and championing practices such as containerization, configuration-as-code, and automated testing
Aligning tooling, processes, and infrastructure with business needs to help teams deliver features faster, respond to issues quickly, and maintain a stable, secure operational posture
Designing and enhancing large-scale data pipelines leveraging Hadoop, HDFS, Apache NiFi, Apache Spark, and Accumulo to support mission-critical data ingestion, processing, and analytics workflows
Optimizing distributed systems performance, improving data reliability, and maintaining resilient ingest and analytic patterns across the Apache ecosystem