Job Description:Airtasker is a fast-growing online and mobile marketplace for local services and temporary labour. We are revolutionising the way people and businesses get more done by connecting real-time labour requirements with one of the world's most under-utilised assets - people power.
Airtasker has big ambitions and recently raised $33M worth of funding as we go international, with the UK being the first country to plant our flag! We are building a talented team with opportunities to make a real impact in a hyper-growth and solutions-oriented start-up workplace.
We are looking for a Data Engineer to join our small but talented Data team. This role will be foundational and critical in setting up core and scalable data infrastructure at Airtasker.
You will be responsible for:
- Working with the Senior Data Engineer in designing, building, future-proofing and operating a scalable data infrastructure
- Working with the Senior Data Engineer in delivering data platform infrastructure, tooling and reporting on a regular basis
- Working with the Senior Data Engineer in understanding the needs of our product teams and delivering valued data models
- Enabling better testing and development workflows
- Supporting the creation of data products that promote customer self-serve
- Work with engineering to ensure the collection of high-quality data
Key attributes we are looking for:
- Previous software engineering experience working in environments dealing with large datasets
- Understanding of modern code-driven data engineering frameworks like Airflow
- Understanding of functional data engineering principles
- Familiarity with testing data pipelines
- An understanding of distributed data processing methodologies, frameworks, and best practices
- Solid understanding of databases and a working knowledge of SQL
- Experience working with Python
- Experience working with cloud products (e.g. S3, Kinesis, SQS, SNS)
- Experience working with Agile methodologies and a cross-functional environment
- Experience with machine learning libraries
- Experience with streaming data