Parkopedia was founded with the mission of being able to answer any parking question, anywhere in the world.
Today, Parkopedia is the world’s leading digital parking services provider used by millions of drivers and organisations such as Apple, TomTom and 18 automotive brands ranging from Audi to VW.
We are looking for Data Engineers to help support our Data Science team’s ingestion, ETL, infrastructure and the productionisation of models. The system is currently responsible for making sense of over a billion data points per day.
Why will you want this job? Because you have a deep love for engineering, want to be in a machine learning and data science ecosystem, and you get a kick from delivering great code into production. You'll enjoy being a valued member of the close knit team where your opinion counts, there is a lot of scope to be creative and come up with new ideas and you'll feel at home working with extremely bright colleagues where learning is a top priority.
Developing automated CI/CD pipelines for Machine Learning products
Creating and improving complex Airflow pipelines
Productionising and scaling code created by Data Scientists
Developing fast and reliable APIs
Developing and deploying Docker containers (Fargate) in AWS using CDK
Building and configuring monitoring tools and dashboards
Championing software best practices, including mentoring junior engineers and data scientists
We are really open to different backgrounds, as what we do is pretty unique, however you really need to have the following as the base:
Minimum of 4 years professional software or data engineering experience or a PhD in a relevant subject
Strong computer science background
Data oriented engineer, attentive to details
Extensive experience in Python
Experience with creating unit and integration tests
Experience with PySpark and working with big data
Also you will have a combination of several of the following skills
Thorough knowledge of the Python data science/engineering ecosystem (e.g. Pandas, Numpy)
Experience working with geospatial data
Experience with AWS, bonus points if you know CDK
Experience with API development, ideally FastAPI or Starlette
Experience with containerisation (e.g. Docker), and container orchestration (e.g. k8s, ECS)
Experience with workflow management tools, ideally Apache Airflow
Experience with setting up CI/CD pipelines, ideally in an ML environment
Experience with Kafka
Experience optimising and preparing for production code initially developed by data scientists
Parkopedia is committed to building a great work environment for all our employees. Here are just a few of the benefits that we offer:
Unlimited annual leave - yup, time off is as important as time in the office, we all need to unwind and recharge our batteries!
Flexible working hours
Annual company retreat
Time off for volunteering
We are an equal opportunities employer and believe in the power of a diverse and inclusive team. We welcome applications from everyone, regardless of race, sex, disability, religion/belief, sexual orientation or age.