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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Developer (Job Code: 1104) - **Company:** Federal Soft Systems Inc. - **Location:** Bentonville, AR, United States - **Experience:** Expert - **Salary:** $107,744.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Software Applications, Microsoft Azure, Big Data, Code Review, Computer Engineering, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Apache Hadoop, Apache Hive, Python (Programming Language), Oracle (Applications), Performance Tuning, Query Optimization, Azure Data Lake, SQL Databases, Teradata SQL, Unstructured Data, Data Processing, Azure Data Factory, Snowflake, Apache Spark, Electronic Medical Records, Git, Data Lakes, Pyspark, Information Technology, Data Lineage, Star Schema, Data Pipelines, Jenkins, Databricks - **Published:** June 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=e6b47572932e8bfd ## About the Role Do you have experience in Spark?, Do you have a Master's degree?, We have job openings available, and we're on the lookout for talented individuals who are ready to contribute their expertise and grow with us., Education: Masters - Computer Science, Computer Engineering, Electrical Engineering, Information Technology, Computer Applications, or in a related field of study (will accept equivalent foreign degree); Training: None; Experience: One (1) year in the position above, as a Senior Software Engineer, as an Application Developer, as a Big Data Engineer, as a Sr. Data Engineer, as an ETL Developer, or in a related occupation; Other Requirements: Experience must include one (1) year use of all the following: Azure, Snowflake, Apache Spark, Hadoop Ecosystem, Python, SQL, AWS, Airflow, Jenkins CI/CD, Git, and data governance/quality tools. Will accept any suitable combination of education, training and/or experience. ## Description Federal Soft Systems Inc. provides an incredible work culture to all the employees. We have a friendly work atmosphere and provide proper guidance for employees to improve significantly. Friendly Work Culture & Environment Flexible Work Time Medical Insurance Learning New Trends & Technologies, Responsible for the design, development, and optimization of data pipelines using Azure Data Factory, Databricks, Spark, and PySpark, ensuring scalable ingestion and transformation of structured and unstructured data; implement and maintain Lakehouse architectures with Delta Lake, Unity Catalog, and Azure Data Lake Storage (ADLS), applying best practices for performance, governance, and security; build and automate CI/CD pipelines with Jenkins, Git, and Airflow, streamlining deployment and monitoring of production-grade data solutions; develop and coordinate data models including Star, and Snowflake schemas, applying partitioning, bucketing, and query optimization techniques for high-performance analytics; leverage cloud platforms including Azure and AWS (S3, EC2, EMR) to support enterprise-scale data processing, migration, and storage solutions; engineer ETL/ELT solutions with SQL, Spark SQL, and Python, enabling efficient integration across Snowflake, Teradata, Oracle, and Hadoop ecosystems; implement Data Governance, Data Quality, and Data Lineage using Ataccama, Manta, and Unity Catalog, ensuring compliance, transparency, and reliability; perform performance tuning of Spark, Hive, and Hadoop jobs to improve efficiency and reduce compute costs; collaborate with stakeholders and Agile teams, gathering requirements, delivering technical documentation, and supporting enterprise decision-making with robust data solutions; utilize and apply knowledge of Azure, Snowflake, Apache Spark, Hadoop Ecosystem, Python, SQL, AWS, Airflow, Jenkins CI/CD, Git, and data governance/quality tools to perform assigned tasks; and lead code reviews and resolve production issues in order to drive reliability and best practices across data engineering initiatives. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Our GitOps approach for deploying an Identity Provider and an API Gateway in a SaaS company](https://www.wearedevelopers.com/videos/776-our-gitops-approach-for-deploying-an-identity-provider-and-an-api-gateway-in-a-saas-company) ## Related Articles - [Is Software Engineering Over-Saturated?](https://www.wearedevelopers.com/magazine/418-is-software-engineering-over-saturated) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Best Countries for Software Engineers](https://www.wearedevelopers.com/magazine/267-best-countries-for-software-engineers) - [Where to Find Entry-Level Software Engineering Jobs](https://www.wearedevelopers.com/magazine/397-where-to-find-entry-level-software-engineering-jobs) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs)