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Partly

Founding Data Engineer

Posted 3 Days Ago
Be an Early Applicant
Australia
Mid level
Australia
Mid level
As the founding Data Engineer, you will design and optimize data pipelines for automotive data, ensuring data integrity and collaboration across teams.
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🚀 Our story

Partly's mission is to connect the world's parts and we're doing that by building the first global platform for replacement parts, starting with auto parts. Our big vision is to accelerate the world towards a sustainable future where waste is eliminated and all replacement parts are universally searchable, accessible and available to all.

Founded by ex-Rocket Lab engineers, we utilise cutting-edge technology to solve challenging but exciting problems that make a huge impact in a $1.9 trillion industry. We've more than tripled our team over the last 12 months and expect to double in size again over the coming 12 months. We're a global team spanning both Europe and Australasia.

We provide a scalable digital infrastructure solution to some of the world's largest businesses and the most exciting startups. Partly's solutions are integrated across hundreds of companies globally, providing the backbone for cataloguing and managing parts online.

Our investors in Blackbird Ventures (Canva, CultureAmp etc.), Square Peg, Octopus Ventures, Hillfarrance, Icehouse, Peter Beck (Rocket Lab), Akshay Kothari (Notion Co-Founder) and Dylan Field (Figma Co-Founder).

We're continuing to build a world-class team and ensuring Partly is a place where people can do the best work of their lives. We're proud of the culture we've built at Partly, and our values are lived throughout every experience.

🖍️ This role

Data in the automotive industry is scattered around the world in a variety of complex formats, and the fun part is in unifying these data into a single format that drives our clients' business.

As the first-ever dedicated Data Engineer at Partly, you will be the technical owner of our data pipelines and infrastructure. You’ll be responsible for designing, building, and optimising robust systems that ingest, process, and deliver data to internal teams and external customers at scale. This includes introducing best practices such as schema versioning, pipeline version control, automated validation, lineage tracking, orchestration, monitoring, and cost optimisation. This is a greenfield project, so you will have the opportunity to have a huge amount of impact.

💻 What will you do
  • Design, build, and maintain scalable data pipelines that ingest, transform, and process automotive parts and vehicle data from multiple sources

  • Partner with Product, Engineering, and Customer teams to deeply understand data needs and ensure customers are set up for success

  • Implement best practices in data engineering — schema management, version control, testing, validation, and monitoring

  • Optimise performance and cost of pipelines and infrastructure while maintaining reliability and scalability

  • Develop visualisations and APIs to surface insights and power customer-facing features

  • Collaborate cross-functionally to solve customer problems and ensure data solutions meet business requirements

  • Build reusable data models and transformation logic to generalise structures for new customers and markets

  • Act as a technical voice for data within the organisation, shaping how Partly builds, manages, and scales its data platform

🥷 Your skills
  • Experience in data engineering — designing, building, and scaling pipelines and ETL/ELT processes

  • Proficiency in SQL and Python (or similar programming languages used for data engineering)

  • Hands-on experience with modern data tools (e.g., Airflow, dbt, Spark, Kafka, Snowflake, BigQuery, Redshift, etc.)

  • Strong understanding of databases and data modelling (relational and non-relational)

  • Experience with cloud platforms (AWS, GCP, or Azure) and data infrastructure management

  • Detail-oriented but also a systems thinker — able to zoom out and design for scale and reusability

  • Strong communicator — able to explain complex data topics clearly to technical and non-technical audiences

  • (Preferred, but not essential) Experience working with e-commerce, automotive, or cataloguing data

  • Ownership mindset — driven to solve problems end-to-end and continuously improve systems

🪅 Benefits
  • High trust, low process and no bureaucracy. We hire exceptional people whose judgment we trust. This means we proactively remove any process or rules that slow us down (for example, our expense policy is simply the “red face test”).

  • Competitive base salary + equity. We offer competitive salaries and generous equity options for all full-time employees, ensuring everyone shares in the financial upside when we win.

  • Flexible working hours. Choose when to work based on what time you’re most effective (no mandatory or set hours). We combine flexibility with an office-first approach (in cities where we have critical mass, i.e. London, Christchurch, Auckland).

  • Focus Days. Two days per week, with zero meetings, dedicated solely to uninterrupted deep work

  • Take time when you need it. We don’t ask questions or care if people have a negative leave balance. We work extremely hard and trust our team to take the time they need to recharge.

  • Offices in London, Christchurch and on Auckland’s Karangahape Road. We invest heavily in our offices (standing desks, healthy snacks, quality coffee, drinks on tap) to ensure they’re places people are excited by, where they build relationships and get their best work done.

  • Learn from the best. Whether it’s during a ‘Lunch n Learn’ or hearing from a unicorn CEO at a Fireside chat, you’ll have the opportunity to constantly learn from the world’s best.

  • Quarterly season openers & annual global offsite. Connect regularly at the nearest centralised location for a week of collaboration, big-picture planning and team events.

  • Team connection. Monthly team lunches, celebrating our wins, happy hours and more!

  • Parental leave and flexible return to work. Do what works for you. Primary carers can return with 4-day weeks (on 100% pay for the first 12 weeks). Secondary carers get 10 days full pay.

  • Payroll Giving: We encourage generous giving and donate to the high-impact charities you support

Top Skills

Airflow
AWS
Azure
BigQuery
Dbt
GCP
Kafka
Python
Redshift
Snowflake
Spark
SQL

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