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Data Engineer

Base Operations

USFull-timePosted 1w agoStill listed 3 days ago

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At a glance

Compensation
No compensation found
Location
US
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Base Operations is building a global dataset of threat patterns and street-level intelligence. The Data Engineer will define, build, and mature data pipelines, models, and a warehouse, contributing to architecture strategy and translating it into tactical plans. The role focuses on reliable data infrastructure that supports analytics, reporting, and the company’s security intelligence objectives.

Skills & qualifications

RequiredNice to have

Skills

Data Engineering, nice to haveExtract Transform Load (ETL), nice to haveSQL (Programming Language), nice to havePython (Programming Language), nice to haveData Warehousing, nice to haveData Modeling, nice to haveData Quality, nice to haveWorkflow Technology, nice to haveAutomation, nice to haveCollaboration, nice to haveProduction Data Pipelines, requiredModern Data Stack Tools, requiredDimensional Data Modeling, requiredWorkflow Orchestration, requiredAutomation Tools, requiredData Governance, requiredGeospatial Data, nice to haveLarge-Scale Datasets, nice to haveWeb Scraping, nice to haveML and AI Infrastructure, nice to haveJavaScript, nice to have

Qualifications

3+ Years Production Pipeline Experience, required3+ Years Data Warehouse Experience, required

Full job description

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.

How this job compares

Set against the 6,283 open Data Engineer jobs on Olive Jobs, counted November 10, 2026.

Pay
  • This postingNot listed
  • US median$125–208K/yr4,868 salary ranges
  • US median$60–72/hr278 hourly ranges
Openings
Olive Jobs lists 6,283 open Data Engineer jobs across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most across the US
Experience
This posting asks for at least 3 years of experience; Data Engineer postings that state a minimum ask for 5 years at the median (5,462 postings).
Education
2,401 of the 6,283 open Data Engineer jobs (38%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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