Senior Backend & Data Engineer

CLOVEHITCH•Dallas, TX

13h•Remote

About The Position

CLGT Solutions, LLC dba CLOVEHITCH is a Service-Disabled Veteran-Owned Small Business focused upon providing professional solutions in the areas of training and talent acquisition. We’re looking for a Senior Backend and Data Engineer who is energized by the challenge of turning disparate, messy, real-world data into structured, scalable, and accessible systems. You will be the primary architect of the "engine room" for our new Reporting Portal—a platform designed to bridge the gap between financial disbursements and physical compliance evidence. This role is ideal for someone who loves working across ingestion, modeling, and workflow orchestration, and who gets satisfaction from designing systems that are resilient, transparent, and easy for others to build on. You will partner closely with a Frontend Engineer to handle the backend data and infrastructure aspects of the product, ensuring that high-volume financial data and unstructured evidence are seamlessly integrated. As you grow in the role, you will lead the implementation of machine learning models and large language models (LLMs) to automate compliance reviews and provide high-speed analytical insights.

Requirements

Experience: 4+ years of professional experience in data engineering or data-focused backend engineering, ideally in a startup or fast-paced context.
Backend Mastery: Strong proficiency in Node.js/Express and writing Python for data workflows.
Modern Data Stack: Deep experience with SQL, data modeling, and workflow orchestration tools.
Cloud Proficiency: Comfort provisioning infrastructure and deploying workflows to cloud platforms (specifically AWS).
Data Technologies: Proficiency across modern storage technologies (PostgreSQL, S3, Lakehouses) and handling varied file formats.
Adaptability: Ability to manage multiple projects, adapt to shifting priorities, and deliver high-quality work on a Fall/Winter 2026 deployment schedule.

Nice To Haves

Experience building and deploying Large Language Models (LLMs) or automated scoring algorithms in a production environment.
Experience with event-streaming architecture (e.g., Kafka/MSK) and API management tools (e.g., Kong or Apigee).

Responsibilities

Data Architecture & Pipeline Development
Medallion Architecture: Design and implement a Medallion-style data architecture (Bronze/Silver/Gold) to manage raw transaction data, immutable snapshots, and curated analytics.
Pipeline Engineering: Build and maintain data pipelines that ingest, clean, and transform data from the Digital Transformation Bridge (DTB) and other sources.
Immutable Audit Trails: Ensure all files and snapshots are stored in a non-destructive environment with strict versioning to preserve original evidence.
Performance Optimization: Implement high-speed querying (e.g., AWS Athena) to enable complex ad-hoc trend analyses against raw data in seconds.
Backend & Infrastructure Engineering
API Development: Build and maintain a high-concurrency backend using Node.js and Express.
Secure Access: Implement robust Identity & Access Control layers, including mandatory Multi-Factor Authentication (MFA) and Role-Based Access Control (RBAC).
Infrastructure as Code: Provision and manage cloud infrastructure using Terraform within an AWS Commercial Cloud environment (EKS, RDS, S3, MSK).
Submission Engine: Develop a robust engine for multi-format uploads (PDF, DOCX, JPEG) featuring draft persistence and real-time validation logic.
AI, ML & Data Science Support
LLM & NLP Integration: Build systems to parse and index unstructured text within uploaded documents using Large Language Models and NLP tools.
Automated Analysis: Develop and operationalize machine learning models to assign compliance "confidence scores" and flag high-risk items for manual review.
Data Science Enablement: Support the internal Data Science Workbench by providing Python notebook access and direct data hooks for risk analysts.
Cross-Team Collaboration
Frontend Partnership: Work daily with the Frontend Engineer to architect data flows, manage APIs, and ensure the UI can handle complex list management and in-browser file rendering.
Stakeholder Communication: Present technical tradeoffs and implementation paths to both technical and non-technical team members.
Agile Ownership: Participate in technical discussions and architectural decisions in an iterative, startup-style environment.