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Arkeus

Data Engineer

Posted 2 Days Ago
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In-Office
Melbourne, Victoria, AUS
Mid level
In-Office
Melbourne, Victoria, AUS
Mid level
Build and maintain ETL pipelines for large volumes of imagery and video data. Perform exploratory data analysis, clean and structure datasets, optimize SQL queries, create prototype visualizations, and ensure data is accurately labeled and ready for machine learning. Collaborate with ML engineers and document datasets, pipelines, and data-quality processes.
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Who we are

Arkeus builds AI-powered sensing systems that help autonomous platforms detect, track and understand what's happening in the most complex and contested environments. Our technology is deployed across defence and national security applications — already protecting lives and strengthening security across the U.S. and allied markets.

Backed by QIC, Main Sequence, R+VC, Salus Ventures, Folklore Ventures, DYNE Ventures and Beaten Zone Venture Partners, Arkeus is entering a major growth phase. We are a small, fast-moving company with the energy and ambition of a start-up and the technical credibility of a world-class defence technology provider.

We work at the intersection of optics, autonomy, robotics and real-time AI and we deploy what we build. If you want to ship technology that matters, not technology that ships decks, this is where you belong.

Check it yourself on News | Arkeus

We have developed an inclusive, transparent and engaging culture that focuses on building a diverse workforce — realising that to attract the very best, we need to ensure our culture is ready to welcome people from all ages, genders and backgrounds.


About the role

As a Data Engineer at Arkeus, you will own the pipelines that turn raw imagery and video from our optical sensing platforms into clean, well-structured data our Machine Learning team can actually use.

You will build and maintain ETL pipelines for large volumes of image and video data, dig into that data through exploratory analysis to understand its quality and characteristics, and make sure everything the ML team touches is trustworthy, well-labelled, and ready to train on.

This is a foundational role — the better the data, the better everything downstream performs.


About you

  • You think in pipelines — you enjoy building the plumbing that makes messy data usable.
  • You're strong with SQL and comfortable working with large, unwieldy datasets.
  • You're fast at prototyping — you'd rather knock out a quick visualisation to understand the data than write a spec about it.
  • You're comfortable working with imagery and video data specifically, not just tabular data.
  • You care about getting data ML-ready, and you understand what "usable" means from a model's perspective, not just a database's.


Key responsibilities

  • Design, build, and maintain ETL pipelines for large volumes of imagery and video data.
  • Conduct exploratory data analysis to understand dataset quality, coverage, and gaps.
  • Clean, structure, and organise datasets so they're readily usable by the ML team.
  • Build fast prototype visualisations to surface data issues and communicate findings to the team.
  • Write and optimise SQL to query, transform, and manage data at scale.
  • Collaborate closely with ML engineers to understand what "training-ready" data actually requires.
  • Maintain documentation of datasets, pipelines, and data quality processes.


Your experience and skills

  • Tertiary qualification in computer science, engineering, data science, or a related discipline.
  • 3+ years of experience in data engineering, data analysis, or a related field, ideally working with imagery or video data.
  • Demonstrated experience building ETL pipelines, ideally with image or video data.
  • Strong SQL skills, with experience managing and querying large datasets.
  • Comfortable prototyping quickly in Python, using libraries such as Pandas, Matplotlib, or similar for exploratory analysis and visualisation.
  • Experience working with unstructured or semi-structured data (images, video, sensor data).
  • Understanding of what makes a dataset ML-ready — labelling, balance, quality checks.
  • Eligible for security clearance.

Desirable:

  • Exposure to computer vision or ML data pipelines specifically.
  • Experience with cloud data storage/processing (e.g. S3, BigQuery, or similar).
  • Familiarity with OpenCV or similar image-processing libraries.
  • Experience with data versioning or annotation tooling.


Why Join Arkeus

  • You will work on the hardest problems in deep-tech — optics, autonomy, real-time AI and hardware-software integration in a single product. The gap between what you build and where it ends up is almost nonexistent.
  • You will collaborate with exceptional leaders who have 40+ years of combined experience in autonomy, optics and defence. You will be learning from — and contributing to — the best in the field.
  • You will become part of a close-knit, ego-free team where ideas compete on merit, not seniority. Low politics, high trust. The kind of team you will still be talking about in ten years.
  • You will work hard and be expected to bring your best — and in return, you will grow faster than you ever would at a large organisation.
  • You will work on technology that is already deployed in real environments — protecting lives and strengthening security across defence and national security applications.
  • You will receive a competitive, market-benchmarked salary, structured career pathways built to grow with you, and the opportunity to participate in our Employee Share Option Plan (ESOP).


If this sounds like you, please apply even if you don't check every box — we care more about how you think than whether your CV is perfect. Join our growing team and help us change the world through autonomous systems.

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