Capital Technology Group, LLC

Technical Writer

• Develop and maintain user manuals, guides, online help content, and process documentation
• Collaborate with engineers, product teams, and subject matter experts to translate technical concepts into clear, user-friendly documentation
• Create technical specifications, training materials, reports, and presentation content
• Manage documentation projects end-to-end, including planning, writing, editing, and publication
• Review and edit content for clarity, consistency, accuracy, and adherence to style guidelines
• Update and maintain documentation based on system changes, user feedback, and release cycles
• Support usability testing efforts to ensure documentation meets end-user needs
• Communicate updates, findings, and project status to stakeholders and business users

Data Engineer

• Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data models
• Develop and optimize AWS-native data platforms using AWS Glue, Amazon EMR, Amazon MWAA (Apache Airflow), Lambda, Step Functions, Amazon S3, Redshift, RDS, DMS, and CloudWatch
• Build high-performance ingestion, transformation, and orchestration workflows for structured and semi-structured data
• Design and optimize analytical data platforms using Amazon Athena, Trino, Hive, OpenSearch, and enterprise data catalog technologies
• Integrate enterprise and external data sources across relational and NoSQL platforms
• Build AI-enabled data solutions using Amazon Bedrock, RAG pipelines, and vector search technologies
• Develop cloud infrastructure using CloudFormation, GitHub, Harness, CI/CD pipelines, SNS, SQS, and EventBridge
• Improve reliability, scalability, performance, and maintainability through monitoring, troubleshooting, automation, and continuous optimization
• Support mission-critical analytics and reporting solutions in AWS-based federal data environments complying with FedRAMP and NIST 800-53 controls
• Lead modernization initiatives migrating IBM DataStage, Hadoop, RunDeck, and shell-based workflows to cloud-native AWS services
• Mentor junior engineers through technical guidance, architecture discussions, and code reviews
• Collaborate with cross-functional teams in an Agile environment to define requirements, deliver data solutions, and communicate technical concepts

Lead Data Engineer

• Develop and implement data quality strategies, standards, testing practices, documentation, and maintenance processes for data pipelines and analytical datasets
• Design and execute automated and manual tests covering data accuracy, completeness, integrity, uniqueness, schema consistency, business rules, freshness, and statistical validity
• Build automated quality checks and integration/end-to-end tests using Python, PySpark/Spark, SQL, and Apache Airflow
• Validate data transformations and pipelines across Apache Spark, Python, AWS, Amazon S3, and related AWS data services
• Develop reusable testing frameworks and utilities for data pipelines and CI/CD, ensuring code and data are validated before production release
• Implement quality validation across raw, cleaned, curated, and analytics-ready data, establishing thresholds, rules, and acceptance criteria
• Investigate data anomalies, schema changes, missing data, pipeline failures, and other quality issues; identify root causes and partner with Data Engineers on resolution
• Conduct code and product reviews and ensure new pipelines and transformations include appropriate unit, integration, and data quality testing
• Monitor data quality metrics and dashboards and support automated regression testing
• Collaborate with Data Engineers, Data Scientists, Analysts, and stakeholders to translate business and regulatory requirements into data quality controls throughout the SDLC
• Support UAT, release validation, production deployments, and documentation of test strategies, requirements, defects, and validation procedures

Quality Engineer, Data

Engineer

• Implement and maintain enterprise Public Key Infrastructure (PKI) services supporting mission-critical federal systems
• Implement and maintain PKI architecture according to technical requirements and guidance of the PKI SME
• Build and maintain CI/CD pipelines using Jenkins and/or Harness
• Automate provisioning and configuration of Windows and Linux infrastructure supporting PKI
• Manage containerized workloads using Docker, Helm, Kubernetes, and EKS
• Administer AWS infrastructure including EC2 and RDS
• Provide user support for certificate lifecycle
• Work across application development, cloud infrastructure, identity, and security domains
• Collaborate with cross-functional teams and stakeholders

Technical Writer

Lead Data Engineer

Quality Engineer, Data

PKI Engineer