Mid-Level DevOps Engineer - HTS Data DerivationHTS 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.
