> Markdown version of [/jobs/ext/3419371-mid-level-cloud-software-engineer-337k-yr-ts-sci-fs-poly](https://www.wearedevelopers.com/jobs/ext/3419371-mid-level-cloud-software-engineer-337k-yr-ts-sci-fs-poly). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Mid-Level Cloud Software Engineer [$337k/yr+] TS/SCI-FS Poly - **Company:** SYSTOLIC, INC. - **Location:** Annapolis Junction, MD, United States - **Experience:** Experienced - **Salary:** $337,000.0 - **Contract:** Permanent contract - **Skills:** Testing (Software), Java (Programming Language), Amazon Web Services, Big Data, Cloud Computing, Databases, DevOps, Elasticsearch, Data Flow Control, Apache Hadoop, MapReduce, Python (Programming Language), Machine Learning, Scala (Programming Language), Search Technologies, Software Engineering, SQL Databases, Systems Integration, Unstructured Data, Apache Spark, Containerization, Kubernetes, Apache Nifi - **Published:** September 12, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9156226/mid-level-cloud-software-engineer-337kyr-tssci-fs-poly ## About the Role * Degree: Technical bachelor's degree or equivalent experience * Years of experience: 6+ years * Total Compensation: $337k+ yearly (tentative) ## Description * Develop advanced cloud software solutions to extract actionable insights and value from structured and unstructured data. * Conduct full lifecycle software development, requirements analysis, system integration, and software testing utilizing modern big data, machine learning, and cloud technologies., * Perform full lifecycle software development, integration, and testing for complex cloud applications. * Implement and maintain dataflow and big data processing pipelines utilizing Java, Python, Scala, NiFi, Apache Spark, Hadoop, Pig, and MapReduce. * Build and manage database architectures, SQL queries, and search capabilities using Elasticsearch and database engineering techniques. * Deploy, manage, and monitor containerized applications in AWS leveraging Kubernetes and DevOps methodologies. * Apply statistical methods and machine learning techniques to process, analyze, and extract insights from large data repositories.