Data Engineer - DataOps

Monks • Cupertino, CA

2d • Hybrid

About The Position

We are seeking a capable, detail-minded Data Engineer with a strong DataOps focus to join our team. In this role, you will be embedded at Monks, serving as a critical delivery partner dedicated to supporting one of our most prestigious, high-profile global client accounts in Cupertino, CA. You will build, scale, and maintain the core data pipelines that deliver trusted sell-through, actuals, and strategic business data to global Sales & Finance leadership. Beyond building your own pipelines, you will play a crucial role in hardening, monitoring, and troubleshooting the team's shared pipeline estate—ensuring high reliability, data quality, and platform performance across production.

Requirements

• 5+ years of Data Engineering experience (or Software Engineering with a strong data focus)
• Expert-level SQL
• Advanced proficiency in Python (Java or Scala is a plus)
• Hands-on experience using Airflow, Spark, Trino/Dremio, Apache Iceberg, Kafka, and Docker
• Experience with lakehouse architectures, query engines, Apache Iceberg maintenance (compaction, snapshot management), and platform upgrade/migration workflows.
• Proven track record designing, deploying, and maintaining custom ETL/ELT pipelines and enterprise data warehouse solutions using version control (Git) and CI/CD pipelines.
• Prior experience working with Sales, Finance, or supply chain data domains (e.g., actuals, sell-through, forecasting) is highly preferred.
• Independently troubleshoot shared production issues, trace anomalies back to their upstream source, and implement durable, long-term fixes.
• High standards for software lifecycle best practices, rigorous separation of dev and prod environments, careful change management, and comprehensive documentation.
• Take pride in data quality and system reliability across the entire team's pipeline estate, not just the code you personally authored.
• Comfortable stepping into ambiguous technical challenges, navigating complex data environments, and driving solutions to completion with minimal oversight.

Responsibilities

• Build & Enhance Pipelines: Develop and maintain efficient ingestion and transformation pipelines from diverse, variable-quality data sources into curated aggregation layers, virtual views, and incremental-refresh logic.
• Workflow Orchestration: Own the code, business logic, and operational health (SLIs/SLOs) of your data products using Apache Airflow to orchestrate, schedule, and monitor workflows.
• Reusable Architecture: Contribute to and leverage shared utility libraries, local validation practices, and scalable coding patterns across the data engineering team.
• DAG Hardening & Resilience: Drive platform-wide reliability by improving preflight cleanup, downstream-refresh stability, table/storage optimization, and failure-alerting flows across shared pipelines.
• Automated Data Quality & Observability: Design and deploy automated Data-Quality Checks (DQCs), custom monitoring pipelines, and troubleshooting tooling that the broader analytics team relies on.
• Platform Governance: Manage asset lifecycles (retiring unused objects), remediate poorly performing queries, optimize materialized reflections, and support engine/orchestrator version migrations.
• Incident Response & Change Management: Own production incident response for assigned domain areas, author clear structured change plans and Root Cause Analyses (RCAs), and maintain operational runbooks.

Benefits

• Excellent, full coverage medical, dental, and vision insurance
• Generous PTO and 15 company-wide holidays
• 401k with company contribution
• Paid parental leave
• Work-life balance with an emphasis on personal well-being
• Career growth in a disruptor space & entrepreneurial opportunities within the Monks network
• A globally diverse & inclusive culture with employee resource groups such as S4 Melanin, Pride.Monks, Cultura.Monks, and more!
• Authentic commitment to DEI efforts and sustainable growth.

What This Job Offers

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