Monks
Data Engineer - DataOps
Cupertino, California, United StatesFrom $150kcontractmidAdded yesterday
About this role
Monks seeks an experienced Data Engineer with strong DataOps expertise to build and maintain critical data pipelines for a high-profile client in Cupertino. You'll design production ETL/ELT systems, manage lakehouse infrastructure, and ensure reliability across shared pipeline estates serving global Sales and Finance leadership.
What you'll do
- Design, deploy, and maintain production ETL/ELT pipelines and enterprise data warehouse solutions
- Build and scale core data pipelines delivering sell-through, actuals, and strategic business data to leadership
- Monitor, troubleshoot, and harden shared pipeline infrastructure for reliability and data quality
- Perform root-cause analysis on production anomalies and implement durable fixes
- Manage Apache Iceberg maintenance tasks including compaction and snapshot management
- Lead platform upgrades and migration workflows with strong change management practices
What they're looking for
- SQL (expert-level)
- Python (advanced proficiency)
- Apache Airflow
- Apache Spark
- Trino/Dremio
- Apache Iceberg
- Kafka
- Docker
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Monks
Monks builds and implements AI-driven solutions within the Google AI ecosystem, helping creative clients prototype and scale innovative workflows. The company is hiring Implementation Engineers to bridge technical and business needs, along with specialized roles in infrastructure support and battery technology validation.
View all jobs at MonksLikely interview questions
- Walk us through a time you diagnosed and resolved a production data pipeline issue—what was your investigative approach?
- Describe your experience designing and maintaining Apache Iceberg tables at scale. How do you handle compaction and snapshot management in production?