Senior Data Engineer - Lead Scalable Data Pipelines & APIs

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

Job summary

SiriusXM is seeking a Senior Staff Data Engineer to design and scale data products and reporting systems across AdsWizz and SXM Media. You will own key data pipelines, APIs, and cloud-based analytics.

You will mentor engineers, lead architecture discussions, and collaborate with product and operations teams to ensure reliable deployments and data quality. Strong hands-on experience with Spark, BigQuery, AWS, and Kubernetes is required.

Qualifications

• 12+ years of software engineering experience in Python or Java.
• 7+ years designing data pipelines with Spark, BigQuery, AWS EMR, and GCP.
• 7+ years crafting REST API-based microservices on AWS.
• Experience with Snowflake and BigQuery.
• Familiarity with Prometheus, Grafana, ELK.
• Experience with data quality frameworks (Monte Carlo, Great Expectations, Soda).
• Experience with Docker and Kubernetes.
• Experience with Kafka, Flink, Pub/Sub.
• Proficiency with Jira and Confluence.
• Strong engineering process and project ownership.

Responsibilities

• Design and build high-performance reporting APIs and data pipelines.
• Lead architecture discussions with ad measurement and revenue data.
• Collaborate with multiple engineering teams in a collaborative process.
• Clarify project scope with product teams and provide direction.
• Ensure production deployments and support incident management.
• Mentor junior engineers.

Skills

Python/Java

Spark

BigQuery

REST APIs

Cloud AWS/GCP

Docker/Kubernetes

Kafka/Flink

Observability tools

ETL/Data quality

Collaboration tooling

Education

Bachelor's Degree in CS/Math

Tools

Snowflake

GCP

AWS

Prometheus

Grafana

ELK

Monte Carlo

Great Expectations

Soda

Kafka

Job description

SiriusXM is seeking a Senior Staff Data Engineer to design and scale data products and reporting systems across AdsWizz and SXM Media. You will own key data pipelines, APIs, and cloud-based analytics.

You will mentor engineers, lead architecture discussions, and collaborate with product and operations teams to ensure reliable deployments and data quality. Strong hands-on experience with Spark, BigQuery, AWS, and Kubernetes is required.