Interested in this Data Engineer role at Zone 5 Technologies?
Apply Now →Skills & Technologies
About This Role
At Zone 5 Technologies, we're redefining what's possible in unmanned aircraft systems. Our team of engineers and innovators is developing cutting\-edge autonomous solutions that push the boundaries of UAS technology \- solving complex challenges that matter.
We're building the future of UAS capabilities, and we're looking for exceptional talent to join us. If you're driven by hard problems, energized by rapid innovation, and ready to make an impact on next\-generation flight systems, you belong here.
We are seeking a Data Analyst to build production\-grade user interfaces and visualization systems for complex autonomy datasets. You will transform data insights into polished, intuitive dashboards, develop frontend components for analytics applications, and create compelling visual narratives that enable engineers to understand flight test results, sensor performance, and system behavior at a glance.
Responsibilities:
Frontend Development \& Dashboard Implementation
- Build responsive, production\-ready web dashboards using modern frontend frameworks (React, TypeScript)
- Develop reusable UI components and visualization libraries for internal analytics applications
- Implement interactive features including filtering, brushing, zooming, and coordinated views across multiple charts
- Create polished user experiences with attention to performance, accessibility, and visual design
- Manage state, data flow, and API integration in complex single\-page applications
Advanced Data Visualization
- Design and implement sophisticated visualizations for time\-series, geospatial, and multi\-dimensional data
- Build custom chart types and interactive graphics tailored to autonomy and flight test use cases
- Develop 3D trajectory viewers, map\-based displays, and sensor visualization overlays
- Create real\-time data streaming visualizations for live monitoring of autonomous systems
- Implement animation and transition effects that clearly communicate data changes over time
UI/UX Design \& Data Presentation
- Design intuitive interfaces that make complex technical data accessible to diverse engineering audiences
- Create visual hierarchies and information architectures that guide users to critical insights
- Develop design systems and style guides for consistent visual language across analytics tools
- Conduct user testing and iterate on designs based on feedback from engineering teams
- Translate data insights into clear visual narratives that communicate findings effectively
Data Integration \& Analytics Tools
- Connect frontend applications to data APIs, databases, and analytics backends
- Implement client\-side data processing and aggregation for responsive user experiences
- Build query interfaces and parameter controls that allow users to slice and filter datasets
- Develop export and reporting features for sharing insights with stakeholders
- Collaborate with data scientists and platform engineers to optimize data delivery for UI performance
Qualifications:
- Bachelor's in Computer Science, Data Science, Human\-Computer Interaction, Design, or related field – equivalent industry experience also welcome
- 5\-8\+ years of experience in frontend development with focus on data\-intensive applications
- Expert\-level proficiency in JavaScript/TypeScript and modern frontend frameworks (React, Vue, or Angular)
- Strong experience with data visualization libraries (D3\.js, Plotly, Recharts, or similar)
- Deep understanding of UI/UX design principles and best practices for data presentation
- Proficiency in HTML, CSS, and responsive design techniques
- Experience with Python for data manipulation and analysis (Pandas, NumPy)
- Understanding of RESTful APIs, GraphQL, and frontend data fetching patterns
- Strong visual design skills and ability to create aesthetically pleasing, functional interfaces
Preferred:
- Experience building dashboards for engineering, robotics, or technical domains
- Familiarity with 3D visualization libraries (Three.js, Deck.gl, Cesium)
- Knowledge of geospatial data visualization and mapping libraries (Mapbox, Leaflet)
- Understanding of time\-series data and real\-time streaming visualization
- Experience with WebGL, canvas rendering, or high\-performance graphics
- Background in interaction design, information visualization, or visual analytics
- Familiarity with design tools (Figma, Sketch) for mockups and prototyping
- Knowledge of accessibility standards (WCAG) and inclusive design practices
- Experience with state management libraries (Redux, MobX, Zustand)
- Understanding of ROS2 data formats or flight test data structures
- Background in statistical visualization or exploratory data analysis
- Experience with testing frameworks for frontend applications (Jest, React Testing Library)
Compensation:
Level III \- $130k \- $157k
Level IV \- $157k \- $187k
What's in it for you:
Benefits:
- Competitive total compensation package
- Comprehensive benefit package options include medical, dental, vision, life, and more.
- 401k with company\-match
- 4 weeks of paid time off each year
- 12 annual company holidays
Why Join Zone 5 Technologies?
- Innovative Environment: Work on cutting\-edge technology that is shaping the future of defense and aerospace.
- Collaborative Culture: Join a team of passionate professionals dedicated to pushing the boundaries of what's possible.
- Career Growth: Opportunities for professional development and career advancement.
If you are passionate about unmanned aircraft technology and want to be a part of a dynamic and growing company, we would love to hear from you. Apply today and join the Zone 5 Technologies team!
*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 form upon hire.*
*Zone 5 Technologies is a federal contractor and participates in E\-Verify to confirm employment eligibility. As required by law, we will verify the identity and employment authorization of all new employees using the E\-Verify system. Learn more about your rights and responsibilities under E\-Verify:* *https://www.e\-verify.gov**.*
Salary Context
This $130K-$187K range is below the median for Data Engineer roles in our dataset (median: $160K across 37 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 3,823 AI roles we're tracking, Data Engineer positions make up 1% of the market. At Zone 5 Technologies, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills Required
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $208,300 based on 266 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($158K) sits 24% below the category median. Disclosed range: $130K to $187K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Zone 5 Technologies AI Hiring
Zone 5 Technologies has 1 open AI role right now. They're hiring across Data Engineer. Based in US. Compensation range: $187K - $187K.
Location Context
AI roles in Austin pay a median of $215,300 across 523 tracked positions. That's 8% above the national median.
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.