Description
Can you imagine building a product that reinvents the way transportation is being used by hundreds of thousands of people every day? Instead of purchasing a vehicle, people use a service to get from A to B. Continue reading this job post to understand how to become a part of a fast-growing startup success story. This is your opportunity to participate in building a cloud-based in-house data analytics platform. You will collect, process and analyze huge amounts of data generated by goUrban mobility solution, all in cloud and using the most modern technologies.
We are about changing transportation how we know it today.
Your place in the team
The goUrban Data Team is looking for a Data Engineer to participate in all aspects of software development of building our cloud based data analytics platform. You'll design, implement and maintain data pipelines, orchestrate data processing computations and, with help of our cloud-ops team, maintain underlying data infrastructure. Also, you will work closely with the team of data analysts and gather their requirements in order to translate them into future features of data analytics platform.
The ideal candidate has hands on experience in backend software engineering in Java ecosystem and data engineering in general. Familiarity with some of (but not necessarily all) technologies listed bellow would be a plus. Our autonomous teams are empowered to take independent decisions so there's a great opportunity for you to learn, grow and have a true impact.
What you would be working on
- Designing, implementing and maintaining data processing workflows
- Documenting source-to-target mappings
- Re-engineering and automating manual data flows to enable scaling and repeatable use
- Building data streaming pipelines and near-real time processing workflows
- Designing, implementing and maintaining ETL processes and pipelines
- Ensuring accessible data for analysis
- Identify data storage requirements
- Creating and maintaining a framework to implement and catalogue business logic in the data analytics platform
- Satisfying ad-hoc data ETL requests
- Recommend continuous improvement of the parts of or the whole data analytics platform based on gathered metrics, user feedback and the cost
Our Tech Stack:
- Data: Python, Bash, SQL, Apache Spark, Snowflake, and more...
- Frontend: React & React-Native, JavaScript & TypeScript, Styled Components, Cypress & Detox
- Backend: Java, Spring Boot, Scala, Akka, PostgreSQL, Cassandra
- Other: AWS, Kafka, Docker, Kubernetes
You think our stack is outdated? Challenge us and propose a new technology that might spice it up.
The goUrban hustle
At goUrban our people come first. Our outstanding culture at work is the first step to build leading products. This mindset and the claim to change global transportation to something better, makes the drive of our people and work environment at goUrban special. Achieving our vision to power new mobility in urban transportation, corporate fleet sharing, rental services and vehicle subscription services requires a long-term commitment we are willing to undertake. This commitment is towards our clients, partners and team. Through constant reflection and dedication to have an impact for a better future of transportation, every single person at goUrban is an ambassador for sustainable and efficient shared mobility.
Benefits we have for you
- Very competitive salaries
- Shared vehicles for private use
- 25 days of holiday
- Hybrid work environment
- Equipment (MAC or PC)
- Team building budget
- Regular company social events
- Once per year international company gathering
- Free parking in the city center
- Truly flexible working hours
- Personal Development Budgets
- ...filled by you
REQUIREMENTS
- Qualifications that are important to us
- 3+ years experience coming from a Data Engineer or Data Analyst background
- Advanced Python skills
- Applied SQL knowledge and experience
- Experience in cloud environments (AWS, Azure…)
- Demonstrated ability to work in a team
- Proven analytical thinking with a natural tendency to use data in decision-making and prioritization
- Usage of Snowflake / AWS Redshift / or any other data warehouse
- Ability to design, implement and maintain data products of non-trivial complexity and data size
- Willingness to use agreed standards and tools to design, code, test, correct and document complex programs and scripts from agreed specifications
- Ability to understand the concepts and principles of data modelling and use these to design and
- Skills to implement relevant data models across multiple subject areas
- Ability to reverse engineer data models from a live system
- Ability to understand industry recognized data modelling patterns and standards
