Data Engineer II - Gen AI - Music
Team: Music
Location: New York, NY
Commitment: Permanent
Workplace Type: remote
What You'll Do
- Build and maintain large-scale data pipelines, including ML pipelines, with data processing frameworks like Scio and Python-based tools on Google Cloud Platform.
- Leverage data engineering best practices in continuous integration and delivery.
- Help drive optimization, testing and tooling to improve data quality and reliability.
- Collaborate with engineers, product managers, subject matter experts, and stakeholders while taking on learning and leadership opportunities that arise every day.
- Work in cross-functional, agile teams to continuously experiment, iterate, and deliver on new product objectives.
Who You Are
- You have at least 3+ years of professional experience working in a product-driven environment.
- You have experience working with high-volume, heterogeneous data using distributed systems and big data technologies such as Python, Scala (e.g., Scio), Ray, Apache Spark, or similar frameworks used for distributed data processing.
- You are proficient in designing and building distributed data pipelines in Python, Scala, or Java, with experience in frameworks like Scio on platforms such as Dataflow.
- You understand data modeling, data access, and data storage techniques, and can apply them to both batch and analytical processing (e.g., using BigQuery for analysis).
- You value iterative software processes, data-driven development, reliability, and responsible experimentation, with attention to cost efficiency and best practices in data engineering.
- You thrive in collaborative environments and enjoy working with cross-functional teams.
- You are a creative problem solver who is passionate about building outstanding products that add real value to millions of people.
- You are enthusiastic about learning more about turning research ideas into products operating at scale
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the Eastern United States region as long as we have a work location.
- This team operates within the EST time zone for collaboration.
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