Software Engineer, Data Engineering

This Software Engineer opportunity is based in Phoenix, Arizona, supporting a large-scale data engineering environment focused on modern cloud and streaming technologies. You’ll work extensively with Google Cloud Platform (GCP), Hadoop, Spark, Kafka, Flink, Python, PySpark, Airflow, Big Query, and related data technologies. This is a 12-month W2 contract opportunity.

This role is a great fit for a data engineer who wants to work at the intersection of cloud modernization, real-time data processing, and scalable data architecture. You’ll have the opportunity to help build and support modern data pipelines, work with lakehouse technologies, and gain exposure to emerging GenAI capabilities while collaborating with an experienced engineering team.

• 2+ years of Software Engineering experience, or equivalent experience through work, consulting, training, military experience, or education
• 5+ years of data engineering experience, including hands-on experience with Hadoop and Google Cloud data solutions
• Experience creating and supporting Spark-based processing and Kafka streaming solutions in a highly collaborative environment
• 2+ years of hands-on experience developing data flows using Kafka, Flink, and Spark Streaming
• 3+ years of experience with data lakehouse architecture and design
• Hands-on experience with Python, PySpark, Apache Kafka, Airflow, and SQL
• Experience with GCP Cloud Storage, Big Query, Dataproc, and Cloud Composer
• 2+ years of experience with No
  
  SQL databases, including columnar, graph, document, and key-value databases and associated data formats
• Public cloud certification such as GCP Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics

• Proven experience migrating data from on-premises environments to cloud-native platforms
• Experience with the Hadoop ecosystem, including Hive, HDFS, Parquet, Iceberg, and Delta Tables
• Deep understanding of data warehouses, cloud data architecture, data pipeline development, and orchestration
• Experience designing and implementing highly scalable, modular data pipelines with built-in data controls and automated data governance
• Familiarity with GenAI frameworks such as Lang Chain and Lang Graph for developing agent-based data capabilities
• Dev Ops and CI/CD experience with Git, Jenkins, Docker, and Kubernetes
• Web-based UI development experience with React and Node.js is a plus

• GCP and cloud-native data engineering
• Hadoop and data lakehouse technologies
• Spark, Kafka, and Flink streaming and processing
• Python, PySpark, Airflow, and SQL
• Big Query, Dataproc, Cloud Composer, and Cloud Storage
• No
  
  SQL databases and modern data formats
• CI/CD, containerization, and Dev Ops tooling
• GenAI frameworks and agent-based data capabilities

• Participate in low to moderately complex Software Engineering initiatives and identify opportunities for process improvement
• Review and analyze tactical engineering assignments and challenges requiring research, evaluation, and selection of technical alternatives
• Develop and support scalable data processing, streaming, and cloud data solutions
• Present recommendations for resolving engineering challenges while exercising independent judgment
• Develop an understanding of applicable functions, policies, procedures, and compliance requirements
• Provide technical information and support to client personnel within Software Engineering
• Collaborate with engineering team members on data architecture, pipelines, processing, and cloud modernization initiatives