Senior Data Engineering Lead for AI‑Ready Cloud Platform

Jobgether SRL; United States; On-site; USD 135,000 - 185,000; Full time

Benefits offered by this job

Remote work opportunity

Medical, dental, and vision coverage

Bonus and commission potential

Holiday and vacation time

Health and wellness days

Birthday leave

Career development

Job summary

Jobgether is seeking a Sr. Manager, Data Engineering in the United States to lead a global data engineering team and own the architecture of a modern data platform.

You will drive data pipelines, governance, and AI readiness across the organization, partnering with business and technology stakeholders. You will champion scalable data solutions using GCP, BigQuery, dbt, Airflow, Python, and SQL while shaping data models and CI/CD practices.

Qualifications

• 3+ years leading data engineering teams and 5+ years hands‑on data engineering in cloud environments.

Responsibilities

• Lead, mentor, and develop a global team of data engineers.
• Own planning, estimation, delivery tracking, and roadmap alignment.
• Establish and enforce engineering and architecture standards for code quality and security.
• Design and oversee scalable data pipelines connecting apps, services, and APIs.
• Lead data engineering across ingestion, transformation, modeling, and consumption using GCP/a related tools.
• Design data models using medallion architecture principles and ensure data quality.
• Drive AI adoption in engineering workflows with practical tools and governance.

Skills

Data leadership

Cloud data platforms

Architectural ownership

Cross‑functional collaboration

AI readiness adoption

Tools

GCP BigQuery

Cloud Composer/Airflow

dbt

Python

SQL

Job description

Jobgether is seeking a Sr. Manager, Data Engineering in the United States to lead a global data engineering team and own the architecture of a modern data platform.

You will drive data pipelines, governance, and AI readiness across the organization, partnering with business and technology stakeholders. You will champion scalable data solutions using GCP, BigQuery, dbt, Airflow, Python, and SQL while shaping data models and CI/CD practices.