Data Engineer

Description

About the company

Power lines, gas pipelines and railways are still inspected the way they were 50 years ago: by helicopter. Expensive, noisy, and up to a tonne of CO₂ per flight hour.

We built the alternative. The HyLighter is a 12-metre autonomous airship running on hydrogen. It flies for up to 10 hours, almost silently, and spots a 1 mm defect from 25 metres up.

But the airship is only half the story. Every flight brings back massive amounts of LiDAR, imagery and methane data, and that’s where the value is. Our AI turns it into what operators act on: 50+ types of defects detected automatically, and leaks pinpointed across their network.

It’s not a prototype. HyLighters already fly missions for France’s largest energy and rail operators and have flown over the Palace of Versailles.

Working at the company

We design, build and fly every HyLighter, and turn its data into insight, all under one roof on a former airbase. Which means:

You own it all the way. At a big aerospace company, you’d own a small piece of one subsystem. Here, you design it, test it, stand on the airfield when it flies, and see the client act on the data it brings back.

Weeks, not years. Ideas go from whiteboard to flight test in weeks.

Responsibility from day one. The founders’ average age is 27. Nobody here waits for permission.

We don’t care about titles or ticking every box. We care about what you build and the perspective you bring, so if your profile is different, apply anyway.

Job Summary

Every HyLighter flight produces a lot of data: LiDAR, imagery, methane data, etc. That data is what we turn into insights for our customers. Between the sensor and the customer insight reporting it goes through a long chain. It is captured by the payload, offloaded into a data upload system in our field trucks after each operation, uploaded to the cloud, ingested, and processed. Every link in that chain has to work, every time.

As a Data Engineer in the data team, you will own that chain from end to end. Your job has two halves:

Run it. Make sure payloads are ops-ready before they fly, that the upload systems in the trucks work in the field, and that every byte captured lands correctly in our pipelines.

Optimize it. Every block in the chain can be cheaper, faster, and more automated. Find where the time and money go, and cut them.

This is a generalist role at the core of the company. One day you're debugging a payload's data capture on the bench, the next you're cutting the cloud cost of a processing step in half. You don't need to know it all on day one. You need to be someone who pushes many topics forward and learns whatever the problem calls for.

Mission

Within the data team, working closely with the Head of Data and hand in hand with the operations and embedded teams, you will:

Run the data chain

Make payloads ops-ready. Define and run the checks that guarantee a payload captures complete, valid data before a mission: sensor health, time synchronization, storage, configuration.

Own the field upload systems. Keep the data upload systems in our trucks reliable. These are the stations we plug the HyLighter into after each operation to offload its data. You'll make offload fast, safe, and foolproof for operators, and make sure the upload to the cloud completes, even with field connectivity.

Guarantee data flows into the pipeline. Monitor ingestion end to end. Detect missing, corrupted, or late data before anyone else does, and make every flight traceable from capture to deliverable.

Be the go-to person when data breaks. Investigate incidents across hardware, network, and software, fix the root cause, and make sure it doesn't happen twice.

Optimize it

Cloud compute and storage. Measure the cost of each processing step and each terabyte stored. Right-size compute and storage tiers, and choose what to keep, archive, or drop.

Connectivity and upload. Reduce what we send and how long it takes: compression, edge pre-processing in the trucks, smarter transfer strategies.

Ops time and manual steps. Find the steps operators and analysts still do by hand (offload, checks, reprocessing) and automate them away.

Track it. Build the dashboards and metrics that show the health and cost of the chain, like cost per flight hour and time from landing to processed data.

Personal Note from Louis (Head of Data)

"Our data chain is where flights become value for our customers, and right now it's held together by a small team that touches everything. I'm looking for someone who loves owning a system end to end: someone who's as comfortable plugging a laptop into a payload as reading a cloud dashboard, and who gets a kick out of making things reliable and then making them efficient. You'll have a lot of autonomy and a direct, visible impact on our operations."

Profile Sought

This role spans two worlds: the hardware in the field and the software in the cloud. You may come from either side, and ideally you have a foot in both. In any case, what matters most is your will to learn the other side. An embedded engineer who wants to learn the cloud is a great fit. So is a software or cloud engineer who wants to get their hands on hardware.

You come from the embedded side

A background in embedded systems, robotics, or hardware-facing engineering, ideally on a product operated in real-world conditions.

You know how things break in the field (power, connectors, storage, clocks, networks) and you design so they don't.

Embedded Linux and SBCs (Raspberry Pi or equivalent), sensors and data loggers, communication interfaces (Ethernet, UART, CAN, USB), time sync (GNSS, PTP/NTP), storage and file systems.

Comfortable on the bench with a multimeter, oscilloscope or logic analyzer, and in the field with a laptop and a terminal.

You come from the software / cloud side

A background in backend, data, DevOps, or SRE, running systems in production.

Object storage (S3 or equivalent), data pipelines, SQL / PostgreSQL, Docker, CI/CD, monitoring and alerting.

Cloud cost optimization, and edge/field connectivity (4G/5G, satellite).

Either way

Solid Python and Linux shell; C/C++ is a plus.

Familiar with recent LLM techniques (agents, tool use, coding assistants) and how to apply them to real workflows.

A track record of end-to-end ownership: you've run something in operations, been called when it failed, and made it better.

An engineering degree or equivalent practical experience. We care about what you've built, not where you studied.

Bonus: geospatial or 3D data (LiDAR pointclouds, GNSS/INS post-processing).

Soft Skills

Generalist mindset. You move across hardware, network, and software without asking whose job it is.

Reliability-obsessed. You'd rather build a check than hope it works, and you write the runbook so the next person doesn't need you.

Cost-aware. You treat money and operator time as engineering constraints.

Autonomous. Hand you a fuzzy problem and you come back with a v1 and the right follow-up questions.

Field-ready. Comfortable in a fast-paced, multidisciplinary team, and happy to go to the trucks when that's where the problem is.

Languages: English is required. French is a plus.

AI Leverage

We're building the company as an AI-native company. That's not a buzzword: it's how we work.

You use AI tools fluently every day: Claude Code, Cursor, Copilot, or whatever gives you the edge.

You look for places where AI can replace a workflow entirely, like data QA, incident triage, or reporting.

Conditions

Office: Base 217, Brétigny-sur-Orge, accessible via RER C. Remote work is part of how we operate, but regular presence on the base and occasional field trips with the trucks are part of the job.

Lab and warehouse access.

Experience: Any (new grads ok)

Visa: US citizen/visa only

Benefits

• Potential to become a shareholder in the company.
• Real ownership and direct impact from day one.
• An excellent work environment: an international team and beautiful offices on a former airbase, with flights happening right outside the window.
• Bi-annual offsite trips with the whole team.
• 100% reimbursement of your public transport pass (Navigo), or €800/year for sustainable commuting.
• A bike provided for commuting.
• Free lunch.
• Access to a sauna and gym on-site.
• Why You Should Join
• Founder mentality: we value extreme ownership and want people who think like founders: fast decision makers, natural problem solvers, and executors.
• Ground floor opportunity: you'll help shape and grow a revolutionary company with the resources to back it.
• Impact and speed: you'll own a system at the heart of how we deliver to our customers.
• Interview Process
• Introductory phone call (20–30 min)
• Technical case study, followed by a debrief with the Head of Data
• On-site meeting with the team (3–4h)
• Reference calls