- Audacity is hiring a Senior Data Engineer to design, build, and maintain
- You will be responsible for ingesting, transforming, and curating data from various
- In this position, you will work with vast datasets, utilizing technologies such
- Your responsibilities will include optimizing existing data pipelines, developing new data models
- This is an exciting opportunity to shape Audacity's data landscape and enable
- Your responsibilities will include optimizing existing data pipelines, developing new data models
- Proven experience with SQL and at least one programming language like Python
- SQL
- Python
- AWS
- Azure
AI-generated summary of what this role requires — see the full description below for the employer's original text.
Audacity is hiring a Senior Data Engineer to design, build, and maintain our large-scale data pipelines and data warehouse. You will be responsible for ingesting, transforming, and curating data from various sources to support analytics, reporting, and machine learning initiatives. This role demands a strong background in big data technologies, ETL processes, and database systems, with a focus on scalability and data quality.
In this position, you will work with vast datasets, utilizing technologies such as Apache Spark, Snowflake, and various cloud-based data services. Your responsibilities will include optimizing existing data pipelines, developing new data models, ensuring data integrity, and collaborating with data scientists and analysts to understand their data requirements. We are looking for a forward-thinking individual who can contribute to our data strategy and infrastructure.
Proven experience with SQL and at least one programming language like Python or Scala for data manipulation is essential. Familiarity with cloud data platforms (e.g., AWS Glue, Azure Data Factory, Google Cloud Dataflow) is highly desirable. You will also contribute to data governance standards and best practices, ensuring compliance and security. This is an exciting opportunity to shape Audacity's data landscape and enable data-driven decision-making across the company.