As a purpose-driven company with a heritage of leading shipping companies, we build and deliver a groundbreaking SaaS solution to change the shipping industry through digitalisation. We strive to help our customers optimise their business while reducing CO2 emissions. This is what empowers us.
Today, we are 150+ employees and more than 38 nationalities spread across offices in Copenhagen HQ, Athens, Varna, Mumbai, Singapore and New York City.
With a recent Series B capital raise of +$50 Mil, we are in a position to challenge the status quo. We proudly support the industry’s green transition and enable our customers to turn data into immediate decarbonisation actions.
What does it mean to be a Data Engineer in ZeroNorth?
As a Data Engineer, you are part of the Data & AI function, where we ensure best practices, technical leadership and career development within the Data & AI space. You are also part of a business domain, where you work in teams together with colleagues with a diverse set of expertise to co-develop a portfolio of customer-facing products.
The teams are staffed cross-disciplinarily with Product Managers, Data Engineers, Data Scientists, Software Engineers, Domain experts, UX Designers and others, who all bring their functional expertise, such that our products excel in all dimensions of our customers’ expectations.
Your responsibility in the team is to help define and build the data infrastructure and be a thought-leader with respect to data engineering best practices for the other engineers in the crew. Together with other Data Engineers across teams you will help shape the data landscape- and data tools in ZeroNorth, to ensure we build scalable products as we grow.
In this role you will
Be part of a product team, collaborating with colleagues from different technical and non-technical backgrounds on shaping and creating value for our customers
Work closely with software engineers, data storytellers and data scientists to enable them to build scalable data pipelines
Help shape our data infrastructure on AWS
Contribute to in-house big data tools and frameworks
Communicate and document outcomes and methodology of works internally and externally to technical and non-technical audiences
Who are you?
3+ years of experience, working with big data solutions such as Snowflake, DBT, Kafka, Airflow, etc. – ideally with experience in AWS cloud solutions S3, batch/EC2, EMR and Glue and with demonstrated business impact
Experience working with collaborative software engineering practices (Git, Agile, DevOps), and methodologies for systematic and continuous analytics delivery (DataOps, MLOps)
Strong expertise in SQL and Python for data processing, ideally also with experience in Spark
Excellent communication skills to share your approaches with a wide range of audiences, from technical peers to product owners
A pragmatic, conscious mindset when trading off development speed versus building fundamentals
Relevant educational background in mathematics, engineering, computer science, etc.
A growth mindset to continuously learn new methods and technologies and eagerness to share knowledge and ideas
We expect you to be self-motivated, accountable, agile and able to balance building perfection vs. building good-enough. Further, you have excellent communication and teamwork skills, and pay great attention to detail.
We expect you to be able to communicate in both oral and written English.
We are ambitious and passionate with an exceptional “Can Do” attitude. We work in a dynamic and informal space with everything you could dream of, such as food, games, fantastic coffee and amazing people. We love what we do - creating apps and services that help scale and optimise everyday challenges. While doing this, we save costs and provide a severe reduction worldwide in CO2 emissions.
We are on a mission for the betterment of our planet, our people, and our company culture. Therefore, we embrace and encourage people from all backgrounds to apply - regardless of race, ethnicity, religion, nationality, gender identity, sexual orientation, age, disability, neurodiversity, socio-economic status, culture or beliefs.