Mid-Level DevOps Engineer - HTS Data Derivation

About the role

Dev Technology is a growing IT company with an employee-centric culture that works on mission-critical projects for the federal government. We partner with our federal customers to deliver technology services and solutions, and to drive our client's missions forward through innovation. We use Agile and DevSecOps principles to provide services including application development, biometrics and identity management, cloud and infrastructure optimization, IT and legacy modernization, and data management. As a Washington Post Top Workplace award winner for the past THIRTEEN years in a row, the Top Workplaces USA for the past five years, and a recipient of the Companies As Responsive Employers (CARE) Award for the past six years, Dev Technology employees enjoy: Generous and flexible time-off policy Flexible work schedules and telework options, including remote work availability for eligible projects Career development opportunities including a mentorship program, technical and management training through Dev University, hands-on learning through DevLab, tuition reimbursement, and paid training opportunities Industry-leading benefits including a choice of two health plans that include dental and vision, flexible spending account, commuter benefits, life insurance, and more 401K matching with a 5% matching contribution Regular team and company social events including our annual party, happy hours, fitness challenges, and more A focus on co

Requirements

• Experience working with HTS or Trade Data pipelines
• Strong Python skills with a focus on data processing, transformation, and pipeline development
• Familiarity with workflow management tools (Nextflow, Snakemake, WDL/Cromwell).
• Understanding of Trade data formats (CSV, Excel, or JSON formats)
• Experience with big data technologies (Spark, Hadoop) or distributed computing.
• Knowledge of data storage solutions for large datasets (object storage, distributed file systems).
• Experience with HPC schedulers (SLURM, PBS, LSF).

Benefits

Additional Information

Mid-Level DevOps Engineer - HTS Data Derivation HTS Data Derivation - Trade Compliance - Federal Data Modernization Location: Hybrid (Onsite in Reston 2 days a week) Clearance: U.S. Citizenship required; ability to obtain a public trust A Role with Purpose and Impact We are seeking a Mid-Level DevOps Engineer to support our federal client, focused on modernizing the Harmonized Tariff Schedule of the United States (HTS). This role requires building and operating a secure, reliable pipeline to ingest, transform, validate, and deliver complex structured datasets. The senior DevOps engineer will own the infrastructure, automation, and security that make high-volume, high-accuracy data delivery possible, which includes support for LLM-assisted quality validation workflows. As a DevOps Engineer , you will: Design, build, and maintain CI/CD pipelines that automate ingestion, transformation, and packaging of HTS datasets Design, implement, and maintain cloud-based infrastructure for data processing in AWS GovCloud. Work with the architect to manage the cloud infrastructure supporting data processing workloads, document storage, and LLM-based validation tooling. Support the OCR and PDF extraction pipeline infrastructure for digitizing historical HTS publications. Build monitoring, alerting, and logging capabilities to track pipeline health, data processing status, and deliverable readiness. Implement automated testing and validation for data pipelines. Coordinate with trade analysts and the project manager to ensure infrastructure supports delivery milestones as per project requirements Promote DevOps best practices, including infrastructure-as-code, version control, and automation. Document systems, architecture, and operational procedures Required Qualifications Bachelor's or master's degree in computer science or Engineering 4+ years of experience in DevOps, SRE, or platform engineering roles. Strong experience with cloud platforms (AWS, Azure, or GCP). Proficiency in scripting languages such as Python, Bash, or PowerShell . Hands-on experience with CI/CD tools (GitHub Actions, Jenkins, Azure DevOps, GitLab CI). Experience with containers ( Docker ) and orchestration ( Kubernetes ). Knowledge of infrastructure-as-code (Terraform, Bicep, or similar). Hands-on experience designing, operating, and maintaining versioned data engineering and machine learning pipelines, with an emphasis on reproducibility, lineage, and controlled releases. Demonstrated experience implementing monitoring and evaluation frameworks for LLM-based systems, tracking output quality, operational cost, and latency.

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