Senior Data Engineer: Scalable Data Pipelines & APIs

Pandora; Oregon (WI); On-site; USD 126,700 - 215,000; Full time

Job summary

SiriusXM is seeking a Senior Staff Data Engineer to design and maintain backend data systems and scalable reporting APIs. You will own data products and collaborate with AdsWizz, SXM Media, and other teams to deliver insights at scale.

Lead architecture discussions, mentor engineers, and ensure reliable deployments across AWS/GCP environments while aligning with product requirements and data governance.

Qualifications

• 12+ years software engineering experience in Python or Java.
• 7+ years designing and building data pipelines with Spark, BigQuery, AWS EMR, and GCP.
• 7+ years crafting REST API-based microservices across cloud platforms (AWS preferred).
• Experience with Snowflake and BigQuery as cloud data warehouses.
• Familiarity with Prometheus, Grafana, ELK; monitoring and observability skills.
• Experience with Docker and Kubernetes; messaging and stream processing (Kafka, Flink).
• Bachelor’s Degree in Computer Science or related field; legal right to work in the U.S.

Responsibilities

• Design and build high‑performance reporting APIs and data pipelines.
• Lead architecture discussions with ad measurement, revenue, and addressability data.
• Collaborate with multiple engineering teams in a cross‑functional environment.
• Partner with Product to refine project scope and requirements.
• Mentor junior engineers and drive projects with ownership and clarity.
• Coordinate production deployments with Cloud Infra and Incident Management teams.

Tools

Python

Java

Spark

BigQuery

AWS EMR

GCP Cloud Analytics

Snowflake

Kubernetes

Kafka

REST APIs

Job description

SiriusXM is seeking a Senior Staff Data Engineer to design and maintain backend data systems and scalable reporting APIs. You will own data products and collaborate with AdsWizz, SXM Media, and other teams to deliver insights at scale.

Lead architecture discussions, mentor engineers, and ensure reliable deployments across AWS/GCP environments while aligning with product requirements and data governance.