Data Engineer IV

Description Hybrid 3 days onsite / 2 remote in Greenwood Village, CO Our client is seeking a Data Engineer IV for the Infrastructure Intelligence and Analytics team to design, build, and maintain scalable ETL pipelines and data infrastructure supporting a data lake, anomaly detection models, and AI agents. The role focuses on Spark and Scala development, onboarding diverse network data sources, ensuring data quality and reliability, and enabling downstream consumers to access well-structured datasets. We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $65.00 to $75.00/hr. w2 JN -082026-108340 Responsibilities Design, develop, and maintain scalable ETL pipelines using Apache Spark with Scala for the IIA Data Lake. Onboard and transform network data sources including telemetry, syslogs, SNMP traps, device configurations, and ticketing systems. Implement monitoring and alerting to ensure pipeline reliability and performance. Develop and manage CI/CD deployment pipelines for data engineering solutions. Manage and optimize data storage across distributed file systems, relational databases, flat files, and API-based sources. Implement data quality checks, validation rules, and automated testing. Optimize performance for large-scale batch and mini-batch processing. Manage schemas, partitioning strategies, and storage formats for efficient querying. Support data backfills and recovery due to upstream issues or schema changes. Collaborate to align solutions with production architectures and business needs. Partner with data scientists and agent developers to deliver datasets for anomaly detection and AI agent workflows. Provide guidance on data engineering best practices. Document and communicate standards and processes to diverse stakeholders. Continuously evaluate and improve tools and approaches. Experience Requirements Proficiency in Python and strong experience with Apache Spark for distributed processing. Scala experience or willingness to learn. Proven experience building and maintaining large-scale ETL pipelines. Experience with AWS services such as S3, Glue, Athena, and EMR. Strong SQL and understanding of relational databases. Knowledge of data architecture, warehousing, partitioning, and columnar formats such as Parquet. Experience implementing data quality and validation frameworks. Experience with workflow orchestration tools, preferably Airflow. Proficiency with Linux and shell scripting. Experience with Git and collaborative workflows. Experience with streaming or mini-batch processing, Spark Streaming, or similar preferred. Experience with Kafka or similar platforms preferred. Experience with NoSQL databases preferred. Telecommunications or large-scale network operations experience preferred. Familiarity with network data sources such as telemetry, syslogs, SNMP traps, and device configurations preferred. Experience with REST APIs and cloud SDKs such as boto3 preferred. Experience writing automated tests for data pipelines preferred. Knowledge of text analysis or log parsing techniques preferred. Education Requirements Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or related field, or relevant experience. Bachelor's degree with 5+ years of data engineering experience or Master's degree with 3+ years of data engineering experience. #J-18808-Ljbffr