Aily Labs, founded in 2020, is an exciting and rapidly growing startup based in Munich and Barcelona. With a team consisting of over 250 passionate and skilled ML Engineers, Data Scientists, and Developers, we are dedicated to our ambitious objective of democratizing AI. We have harnessed cutting-edge technology to develop an exceptional AI mobile app that goes beyond conventional solutions. By seamlessly providing immediate business insights, we are poised to revolutionize the corporate landscape. Our vision is to establish ourselves as the preferred platform for AI-driven decision-making, setting new standards in the industry. We firmly believe that our state-of-the-art technology empowers organizations to make faster and more intelligent choices. By joining our team, you will have the opportunity to be at the forefront of this transformative movement, shaping the future of intelligent decision-making in remarkable ways.Key Responsibilities
If you have a passion for data and technology and want to join a crew of sharp analytical minds and data enthusiasts, then this may be the right opportunity for you. As a Data Practitioner, you will take part of the following tasks:
Develop high quality data models in SQL to support our applications
Develop well defined, performant and documented DBT models.
Design, building, and launching of new data models and data pipelines.
Implement best practices in data engineering including data integrity, validation, reliability, and documentation and improving discoverability of data
Optimize database design for performance
Develop automated data pipelines in AWS (Lambdas, Glue, EKS)
Design and build new ways on ingesting and providing data (API, 3rd party integrations).
Implement muti-tenant data architecture systems.
Build relationships with Data Scientists, Product Managers and Software Engineers to understand data needs
Qualifications/ Experience
1 year + of relevant Data working experience
Coding skills in Python and SQL
Knowledge of Data tooling (Airflow, DBT, S3, RDS, …)
Ability to build workflows in Airflow with operators, dependencies, and error handling. Implements proper scheduling and triggering conditions
Understands and can follow data design principals.
Good understanding of GIT (branching, merging and rebase)
Ability to communicate complex concepts concisely and clearly
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