Mid-Level DevOps Engineer - HTS Data Derivation

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.

Preferred Qualifications

• 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).

Our estimated salary range for this position is $90,000-$130,000. This presented salary range is not a guarantee of compensation or salary. Offered salary is based on education, experience, geographic location, and possibly contractual requirements as appropriate to the role. *Salary could fall outside of this range.