Data Engineer Software Developer - Rmantras with Security Clearance

RMantra Solutions; Illinois; On-site; USD 110,000 - 160,000; Full time

Job summary

RMantra Solutions is seeking a data engineer to design, build, and maintain scalable data systems for analytics and reporting. You will unify diverse data sources into an accessible platform, implement Kafka and Elastic Stack solutions on AWS/OpenShift, and optimize pipelines for performance and cost.

You will develop data warehouses and lakes, automate ETL/ELT, and collaborate with analysts and engineers across teams.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related technical discipline and 4+ years of relevant experience.
• Hands-on experience designing, building, and maintaining data pipelines (ETL/ELT) and integrating multiple, disparate data sources.
• Experience with data warehouse and/or data lake technologies (e.g., AWS Redshift, S3, Hadoop, Snowflake, or similar).
• Proficiency with data engineering tools and languages such as Python, Java, SQL, and shell scripting.
• Experience with Elastic Stack (Elasticsearch, Logstash, Kibana) and/or Kafka for data ingestion and processing.
• Familiarity with network operations data (logs, metrics, events, ticketing, CMDB) and related data models.
• Experience with Linux/UNIX system administration and automation.
• Knowledge of data security, access controls, and compliance frameworks (DoD, DISA, RMF, STIGs).
• Experience with CI/CD pipelines, containerized pipelines, version control (Git, Bitbucket), and DevOps practices.
• Strong communication and documentation skills for collaboration and knowledge sharing.

Responsibilities

• Designs, builds, and maintains scalable data systems and pipelines for analytics and reporting.
• Unifies and integrates data from multiple networks into a consistent, accessible platform.
• Implements solutions using Confluent Kafka, Elastic Stack, AWS, and OpenShift/Kubernetes.
• Develops and manages data warehouses and data lakes to support analytics and dashboards.
• Optimizes ingestion throughput, query performance, and storage efficiency across Elastic and Kafka.
• Automates ETL/ELT, data validation, cleansing, monitoring, and supports CI/CD pipelines.
• Collaborates with data analysts, visualization engineers, and stakeholders; documents architecture.
• Troubleshoots issues related to ingestion, processing, platform performance, and storage.
• Applies knowledge of system architecture and centralized logging (ELK) to data transformation.

Skills

Python

Java

SQL

Shell scripting

Elasticsearch

Kafka

Spark

ETL/ELT design

Data integration

DevOps practices

Education

Bachelor’s degree in Computer Science, Engineering, or related technical discipline

Tools

AWS

Redshift

S3

Hadoop

Snowflake

Kubernetes

Docker

Git

Bitbucket

CI/CD tooling

Job description

Primary Responsibilities

• Designs, builds, and maintains scalable, reliable data systems and pipelines to ingest, process, and transform large, complex, and disparate data sources for analytics and reporting.
• Unifies and integrates data from multiple network operations systems into a consistent, accessible platform, ensuring data quality, accuracy, security, and compliance with DoD and DISA requirements.
• Implements solutions using Confluent Kafka, Elastic Stack, AWS, and Red Hat OpenShift (Kubernetes), including creating Kafka, Elastic, and Logstash pipelines and supporting Kibana visualizations and dashboards with React, JavaScript, and HTML.
• Develops and manages data warehouses and data lakes to support analytics, reporting, and operational dashboards, optimizing infrastructure for performance, scalability, and cost-effectiveness through automation and best practices.
• Continually analyze and optimize ingestion throughput, query performance, indexing strategies, and storage efficiency across Elastic and Kafka platforms.
• Automates data-related tasks such as ETL/ELT processes, data validation, cleansing, monitoring, and supports CI/CD pipelines for automated build, test, and deployment.
• Collaborates with data analysts, visualization engineers, and other stakeholders to deliver integrated, actionable data solutions, and documents data architecture, integration patterns, and operational procedures.
• Troubleshoots and resolves issues related to data ingestion, processing, and platform performance, storage, memory, partitioning, and cluster performance.
• Apply knowledge of system architecture, networks, and centralized logging (ELK) to support data transformation initiatives.

Basic Qualifications

• * Bachelor’s degree in Computer Science, Engineering, or related technical discipline and 4+ years of relevant experience.
• Hands-on experience designing, building, and maintaining data pipelines (ETL/ELT) and integrating multiple, disparate data sources.
• Experience with data warehouse and/or data lake technologies (e.g., AWS Redshift, S3, Hadoop, Snowflake, or similar).
• Proficiency with data engineering tools and languages such as Python, Java, SQL, and shell scripting.
• Experience with Elastic Stack (Elasticsearch, Logstash, Kibana) and/or Kafka for data ingestion and processing.
• Familiarity with network operations data (logs, metrics, events, ticketing, CMDB) and related data models.
• Experience with Linux/UNIX system administration and automation.
• Knowledge of data security, access controls, and compliance frameworks (DoD, DISA, RMF, STIGs).
• Experience with CI/CD pipelines, containerized pipelines, version control (Git, Bitbucket), and DevOps practices.
• Strong communication and documentation skills for collaboration and knowledge sharing.
• Must be able to commute to Scott AFB, IL for up to full-time onsite support.
• Ability to obtain interim Secret DoD Security clearance before the start date.
• Ability to obtain Security+ certification or equivalent DoD 8570 IAT II certification within 14 days of the start date.

Required Skills

• Experience with DISA, DISN, or other DoD network environments, including developing and deploying software applications that meet DoD security standards (e.g., STIGs), and knowledge of network security, encryption, and access controls in classified environments.
• Experience with big data technologies and platforms such as Kafka, Spark, NiFi, Hadoop, Elasticsearch, Logstash, Databricks, and ELK Stack for text mining, summarization, search, and entity extraction.
• Experience with cloud-based data platforms (AWS, Azure, GCP, AWS GovCloud), cloud-integrated platforms, and infrastructure as code, including networking and security policies.
• Familiarity with Kubernetes deployment, platform upgrades, patching, configuration management tools (Ansible, Puppet, Chef), and monitoring, alerting, and observability tools (Prometheus, Grafana, Elastic).
• Experience with BI tools like Kibana and developing and maintaining technical documentation and runbooks.
• Strong understanding and practical experience with Agile methodologies (Scrum, SAFe), and related tools such as Atlassian JIRA and Confluence.
• Certified Confluent Developer and Certified Elastic Engineer.
• Excellent communication and collaboration skills, with experience working remotely with geographically dispersed teams and within a matrixed organization to combine software, integration, and data engineering practices.