Description

You will build and scale data infrastructure to support batch and real-time processing of billions of records.

Responsibilities

• Architect scalable systems and document technical solutions to meet business requirements.
• Build and automate cloud infrastructure, services, and observability.
• Develop CI/CD pipelines and testing automation to enable iterative improvements.
• Interface with data scientists, product managers, and stakeholders to promote data best practices.
• Perform data mining and analysis to provide insights on product usage, funnel metrics, and revenue growth.

Required Skills

• 4-7 years of industry experience in big data systems, data processing, and SQL databases.
• 3+ years of experience with Spark data frames, Spark SQL, and PySpark.
• 3+ years of hands-on programming with Python and SQL to write modular, maintainable code.
• Strong understanding of dimensional modeling and analytical big data warehouses like Hive and Snowflake.
• Experience with ETL workflow management tools such as Airflow.
• 2+ years of experience building reports and dashboards using BI tools like Looker.
• Proficiency with version control and CI/CD tools including Git and Jenkins.
• Experience analyzing data using notebook solutions like Jupyter, EMR Notebooks, or Apache Zeppelin.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Key Skills

Education

Bachelor’s degree in computer science