Senior Big Data Engineer

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Design, develop, and maintain scalable data processing solutions using Python and Apache Spark across on-premises and cloud environments. Optimize Spark jobs for performance and resource utilization. Build scalable, fault-tolerant data pipelines with monitoring, alerting, and logging. Use AWS cloud services to manage data pipelines and distributed workloads. Develop and optimize SQL queries for relational and data warehouse systems. Apply best practices for data modeling and distributed system performance. Use Git for source control and maintain unit and integration tests. Collaborate with teams to translate business requirements into technical solutions. Analyze large datasets to extract insights. Mentor junior engineers and conduct code reviews. Requirements include 5+ years in software development with Scala, Python, or Java, experience with Apache Spark, Hadoop, Hive, AWS, Databricks, Kubernetes, Docker, Airflow, and machine learning. BA/BS in Computer Science or related field required. Preferred experience with Databricks platform and ELK stack. Salary range: $88,900 to $165,100 annually. Location: Westminster, Colorado, United States.