Lead Data Engineer: Cloud-Native Lakehouse & Data Quality

Jobtailor; California (MO); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Job summary

Jobtailor is seeking a senior Data Engineering Leader to drive architecture and delivery of data platforms in the cloud. You will shape lakehouse architectures, establish reusable ingestion/transformation patterns, and implement data quality, observability, and security practices.

You will also mentor a data engineering team, champion operational excellence, and collaborate across teams to ensure scalable, compliant data pipelines across AWS, GCP, and Azure.

Qualifications

• Bachelor’s degree in a relevant field.
• 8+ years of hands-on data/software engineering experience.
• Experience delivering production data platforms and pipelines in cloud environments.
• Architecting and building cloud-native data platforms (AWS, GCP, Azure).
• Designing scalable batch and streaming data pipelines.
• Implementing operational excellence.

Responsibilities

• Lead the architecture and delivery of data engineering capabilities.
• Design and evolve lakehouse-style data architecture.
• Establish reusable patterns for ingestion and transformation.
• Define and run data quality and observability practices.
• Build security, privacy, and compliance into pipelines.
• Lead and mentor the data engineering team.

Skills

Data Engineering Leadership

Cloud-Native Data Architecture

Data Pipeline Design

Data Quality Practices

Operational Excellence

Team Leadership

Mentoring

Education

Bachelor's degree in a relevant field

Tools

AWS

GCP

Azure

Job description

Jobtailor is seeking a senior Data Engineering Leader to drive architecture and delivery of data platforms in the cloud. You will shape lakehouse architectures, establish reusable ingestion/transformation patterns, and implement data quality, observability, and security practices.

You will also mentor a data engineering team, champion operational excellence, and collaborate across teams to ensure scalable, compliant data pipelines across AWS, GCP, and Azure.