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Salary
≈ $89k – $165k per year (Estimated)
Location
Remote (United States)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Oct 29, 2026.

Overview
Company
Impact
Profile match
Base Operations decodes the world’s threat landscape into actionable security insights to protect your people and assets around the world.

Base Operations - Data Engineer

Location: US-based, Remote

Who We Are:

Base Operations decodes the world’s threat landscape into actionable security insights that enable organizations to protect their people, assets, and operations. We empower security teams to better assess threats, manage risk across large footprints, and make data-driven decisions using granular, street-level intelligence.

As a category-creator in a growing market, we are looking for impact-driven individuals who are passionate about technology and are committed to helping our customers operate with efficiency and greater accuracy. We developed our technology at Harvard and MIT and use cutting-edge AI. The company is award-winning and backed by top-tier VCs. Our customers include some of the most sophisticated and relevant companies in the Fortune 500. Our team cares about solving hard problems, promoting transparency, encouraging growth in emerging markets, and empowering people to safely explore the world. We are a thoughtful, dedicated, and fun-loving group obsessed with disrupting the security intelligence industry and winning the loyalty of our customers.

Overview:

Base Operations is building the world’s largest dataset of global threat patterns and street-level intelligence. We are looking for an exceptional data engineer that can define, build, and mature the data pipelines, models, and warehouse to help us excel in this objective. This individual should have the technical acumen to contribute thought leadership relative to our architecture strategy, while also excelling at mapping that strategy into a tactical plan and executing against it.

RESPONSIBILITIES

You will:

  • Build, test, and maintain robust ETL pipelines for structured and unstructured data sources, including integration with ML models for data enrichment, with focus on production stability, performance optimization, and incident resolution

  • Develop data transformation, validation, and quality monitoring processes to ensure reliable and actionable data

  • Design and implement data warehouse solutions and data models to support analytics and reporting needs

  • Establish data quality frameworks with monitoring, alerting, and remediation processes

  • Contribute to overall data architecture decisions and lead implementation of data platform improvements

Required Experience

  • 3+ years experience building production data pipelines and working with modern data stack tools

  • 3+ years implementing and maintaining data warehouses and dimensional data models

  • Strong SQL skills and experience with data modeling best practices

  • Proficiency in Python for data engineering tasks

  • Experience with workflow orchestration and automation tools

  • Experience implementing data quality and governance practices

  • Strong collaboration skills working with data scientists, analysts, and engineering teams

Preferred Experience

  • Experience working with geospatial data

  • Working with large-scale datasets

  • Experience with web scraping

  • Understanding of ML and AI based infrastructure

  • Familiarity with JavaScript

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire.

Base Operations champions diversity - we welcome and employ people regardless of race, color, ancestry, religion, gender, gender identity, genetic information, parental or pregnancy status, national origin, sexual orientation, age, citizenship, marital status, disability, or Veteran status. We are proud to be an equal opportunity employer.

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