Role: Sr Data Engineer
Location: Sunnyvale, CA /San Diego, CA (Hybrid)
Duration: Long-term contract
Job Description:
Why They're Hiring:
The team has built a large-scale data platform over the past 8+ months and needs an additional engineer to continue scaling it.
This person will own new feature development while also maintaining existing production data pipelines. The work enables downstream AI/ML teams by providing clean, reliable datasets generated from the client's cellular hardware logs.
This is an infrastructure-focused Data Engineering role-not an ML Engineer or Data Scientist position.
What the Team Does:
The Cellular Systems Engineering team captures and processes enormous volumes of log data generated from devices during hardware validation and testing.
Historically, only "bad" logs (known failures) were stored due to storage limitations.
Their new platform now stores both "good" and "bad" data at massive scale, so AI/ML teams can identify hidden reliability issues and improve future silicon and cellular hardware designs.
Primary Responsibilities:
* Design and develop large-scale data pipelines
* Build scalable ETL/data ingestion solutions
* Curate and transform raw datasets
* Maintain production data pipelines
* Improve reliability and observability
* Design new infrastructure features
* Work directly with internal customers using the platform
* Build solutions while requirements continue to evolve
* Own projects end-to-end with minimal direction
Required Technical Skills
Must Have:
* Apache Spark
* Trino (Presto)
* Apache Airflow
* AWS
* SQL
* Large-scale Data Engineering
* Distributed Computing
* AWS Knowledge- Does NOT need to be an AWS expert.
Should understand:
* S3
* IAM Roles
* IAM Policies
* RBAC / Permissions
* Data governance
