Description

You will design, develop, and maintain a multi-terabyte product and event analytics platform processing billions of records daily in real-time.

Responsibilities

• Design and maintain real-time data pipelines and event-driven systems to support analytics.
• Partner with product engineering to improve data collection mechanisms and analytics client efficiency.
• Lead technical design discussions and provide leadership to the data engineering team.
• Monitor the data platform and recommend architectural enhancements.
• Collaborate with analysts and stakeholders to define technical requirements and prioritize project intake.

Required Skills

• 5+ years of engineering experience.
• 2+ years of experience in scalable data architecture, fault-tolerant ETL, and cloud-based data quality monitoring.
• Deep understanding of distributed data processing using Kafka and Spark.
• Proficiency in Python, Java, or SQL.
• Experience with Airflow, Celery, or other Python-based task-processing systems.
• Strong knowledge of data modeling concepts, design patterns, and coding best practices.
• Proficiency with Git and modern source control systems.
• Experience working with non-technical business stakeholders.

Preferred Skills

• Cloud-based DevOps experience with AWS, Google Cloud Platform, or Azure.
• Experience with Amplitude, Snowplow, or Segment.
• Relational database design and Snowflake or other distributed columnar-store databases.

Key Skills

Education

ANY GRADUATE