Data Engineer impacting music.
Data Engineer impacting music
700000 - 850000 per annum|
This is an opportunity to empower the world of entertainment and connect artists with fans everywhere and anywhere.
Music and Art have played a major part in everyday life, and has previously helped shape cultures, languages and borders around the world.
Artists globally now compete for fans attention and engagement, but fan consumption is fragmented across multiple platforms, and this is an opportunity to now connect everything in one place….Connect billions of fans with the content they love!
Working closely with major music labels, major stars and even a up-and-coming future stars you will help impact their careers by joining one of the world's leading off platform entertainment discovery networks and helping them continuously evolve further.
This is a company of over 100 developers, engineers, PM's and more that are located in every corner of the globe with the common denominator being a passion for Music and Art!
Now seeking a Data Engineer to support their mission of creating value through data
Overview of technology in data pipelines:
- Storage: Snowflake, Druid, Microsoft SQL Server, MySQL, PostgreSQL, S3
- Messaging: AWS SQS, Kafka, Azure Service Bus
- Orchestration: Airflow, AWS Glue
- Languages: Python, Bash
- Deployment: Docker, Kubernetes
- Collaborate with product managers, designers, and researchers in your cross-functional team to discover new features and products, leveraging the billions of data points they are processing every month
- Setup and maintain your team's technical infrastructure (e.g. data lakes, warehouses, and databases)
- Create production-ready, scalable data pipelines
- Architect, code, and test backend services to support machine learning training and inference at scale
Required abilities and skills:
- You have extensive experience in designing and building complex data processing systems.
- You have significant development experience and interest in Python.
- You have experience in creating a performant infrastructure for data collection, storage, processing, and exposure, especially including orchestrating and monitoring data pipelines, preferably with AWS.
- You have experience working with Kafka, Airflow, and Snowflake.
- You have experience using Docker and Kubernetes.
- You can proficiently communicate technical concepts.
You can expect
- A modern and flexible employer
- Fully remote role or paid relocation to Copenhagen
- Monthly budget for mental and physical wellness
- Catered lunch if in office
- 25 days of vacation days not including the festivals you would attend during work!
- International and diverse team with office locations around the world
- Social and team events
- Laptop and phone compensation
- Competitive salary + fringe benefits (Pension, etc)
Darwin Recruitment AG is a Zurich based, SECO licensed, privately owned subsidiary of Darwin Professional Staffing Group Ltd (a Global IT Recruitment Consultancy).
Darwin Recruitment AG manages client relationships whilst also utilising Darwin Professional Staffing Group databases and networks to source Candidates and fulfil client requests.
We do not ask for a placement fee from Candidates/Employees.
If you wish to contact a specialist regarding this role, or your job search in general, please contact +41 (0)43 456 29 09
SUBMIT YOUR CV
SIMILAR JOBS IN Data Engineering.
Lead Azure DevOps Engineer
Apply Now We are looking for a Lead DevOps Cloud Engineer to join one of our clients in the Randstad...
Data Engineer - Java/Python
Apply Now ***Required: A new Data Engineer to work for my client*** If you've got a background in working with...
Senior Machine Learning Engineer
Apply Now Our client has extremely data-driven strategy, therefore the job will require close cooperation with Product managers to drive...
USE OUR ONLINE PLATFORM TO ACCESS ALL THE INSIGHTS THAT YOU NEED...
• Salaries; split by technology and seniority level.
• Time to hire; how long it takes to secure and start a new role, or source and hire talent.
• The average tenure of professionals per tech specialism.
• Gender split per location and tech specialism.
• Fastest growing skills per tech specialism.