Senior Manager, Data Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Data Quality & Observability: Develop and uphold a strong data quality culture that includes lineage, freshness monitoring, anomaly detection, and outcome-focused, gaming-resistant quality metrics.

• Self-Serve Platform: Spearhead the development of a self-service analytics platform to minimize custom request volumes and enhance partner-team independence.

• Cost & Efficiency: Manage the unit economics of the data platform, focusing on compute and storage efficiency while driving tangible improvements without compromising reliability.

• Cross-Functional Partnership: Collaborate closely with Data Science, BIE, Analytics, Product, Data Platform, and the CTO organization to establish the semantic layer, modeling standards, and data contracts that ensure trustworthy and efficient downstream work.

• Engineering Culture: Implement stringent engineering best practices, including code reviews, testing, CI/CD for data, incident response, and postmortems, while promoting the effective and measured utilization of AI coding tools to enhance engineering productivity.

• Team Leadership: Guide, mentor, and develop a high-talent-density team of data engineers, cultivating a culture of ownership, technical excellence, psychological safety, and ongoing learning.

⛳️ Requirements

• 8+ years of experience in data engineering or backend/data infrastructure, with progressively increasing responsibilities, preferably in high-scale environments.

• 3+ years of hands-on experience in managing and developing engineering teams, which includes hiring, coaching, performance management, and team structuring.

• Deep Technical Expertise: A solid track record of building and managing large-scale batch and streaming pipelines (e.g., Spark, dbt, Airflow/orchestration) within a modern lakehouse or warehouse architecture (e.g., Databricks, Snowflake, BigQuery).

• Reliability & Quality: Proven accountability for data SLAs, observability, lineage, and incident response for critical business pipelines.

• Systems & Modeling: Strong fundamentals in data modeling with the capability to design a semantic layer and data contracts that cater to multiple downstream users.

• Stakeholder Management: Exceptional communication skills and the ability to align engineering, data science, analytics, and business stakeholders around common reliability and quality objectives.

🏝️ Benefits

• This role is not available in Zone 1

• US Zone 2: $202,700 - $274,300 USD

• US Zone 3: $180,200 - $243,800 USD