Beatdapp is a venture-backed startup delivering the most advanced music tracking and fraud detection technology in the world. Ranked #2 startup in Canada and Top 20 Music Companies globally, our industry-leading software helps artists and labels track and audit their media streams for royalty payments. Our fraud detection tools help streaming services identify and fight bots and bad actors!
Plus, who doesn't love working with the world’s best music labels and artists all day!
Data Engineer
As a Data Engineer, you’ll work closely with our leadership team, data scientists, and product team to facilitate the development of supervised and unsupervised models that help identify and fight fraud across music streaming services. You will directly influence our product decisions and help to fight a multi-billion dollar problem plaguing the music industry.
Major responsibilities
- Build data pipelines to feed machine learning models for large-scale use cases
- Work closely with Data scientists to scale model training and explore new data sources and model features
- Build integrations with 3rd party vendors and platforms
- Identify opportunities to streamline, automate tasks, and build reusable components across multiple use cases
- Create dashboards that help our stakeholders understand the performance of the experiments and help them make decisions
Successful Candidates will have
- 2+ years of experience as a Data Engineer or in a similar role
- 2+ years of experience with SQL and Python, Javascript, R, or similar
- Experience with data modeling, data warehousing, and building ETL pipelines
- Experience using cloud platforms like AWS, GCP, or Azure
- A drive to learn and master new technologies and techniques
- Strong problem solving skills with an emphasis on product development
Preferred Qualifications
- Experience with Apache Spark, Apache Airflow, Kubernetes
- Experience with GCP technologies like BigQuery & Vertex AI
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Perks
- Working on difficult problems with a team that will push your thinking
- Joining a growing company with a strong foundation, leading in its field
- Frequent company events and offsites
- A flexible work environment