Senior Data Engineer, Data Products

Raya • Los Angeles or Remote, CA

4h

About The Position

A great candidate is excited to support our growing use of data, including working closely with the analytics and product engineering teams, to build a better user experience. Finally, they believe in Raya’s vision, which is to enrich lives by fostering relationships through quality, in person interactions. As Raya’s first Data Engineer for Data Products, you will be a founding member of the data engineering team and will play a pivotal role in empowering the company to be data-driven. The ideal candidate is experienced and confident building out performant, impactful data models, and trhives in a collaborative environment where they can influence product and business decisions through data. In this role, you will Architect complex, high-volume data pipelines for production use. Design and implement scalable data models serving multiple product and internal teams. Own data quality frameworks and standards across key data products. Build reusable patterns for transformations and metrics to drive efficiency. Define and maintain core business metrics and Key Performance Indicators (KPIs) in partnership with Analytics. Own the data products used across the company, ensuring reliability and performance. Set and promote standards for data modeling and pipeline development. Partner closely with Analytics, Data Science, and Machine Learning teams on requirements to reduce friction and accelerate their work. Mentor engineers and actively participate in the hiring process.

Requirements

• 5+ years of experience in data engineering with a proven track record of successful data architecture and pipeline creation.
• Expertise in handling large-scale data systems and cloud platforms (preferably AWS).
• Proficient in Python and SQL.
• Strong experience with data pipeline and workflow management tools like Apache Airflow, Luigi, or Prefect.
• In-depth knowledge of real-time data processing frameworks such as Kinesis, Kafka, Flink, or Spark Streaming.
• Experience with data modeling tools and ETL frameworks, with a strong emphasis on performance optimization.
• Excellent communication and collaboration skills to work effectively across teams.

Nice To Haves

• Scala and MongoDB are a plus
• Experience with Segment is a plus.

Responsibilities

• Architect complex, high-volume data pipelines for production use.
• Design and implement scalable data models serving multiple product and internal teams.
• Own data quality frameworks and standards across key data products.
• Build reusable patterns for transformations and metrics to drive efficiency.
• Define and maintain core business metrics and Key Performance Indicators (KPIs) in partnership with Analytics.
• Own the data products used across the company, ensuring reliability and performance.
• Set and promote standards for data modeling and pipeline development.
• Partner closely with Analytics, Data Science, and Machine Learning teams on requirements to reduce friction and accelerate their work.
• Mentor engineers and actively participate in the hiring process.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed