Remote Senior Data Engineering Lead

YipitData; United States; Remote; USD 170,000 - 215,000; Full time

Benefits offered by this job

Flexible work hours

401K match

Parental leave

Job summary

YipitData is seeking a Senior Data Engineering Manager to lead a global data engineering team responsible for large-scale data pipelines and production datasets. You’ll own data architecture, guide implementation, and collaborate with product and research teams to deliver reliable data assets and AI-ready datasets.

This role emphasizes hands-on leadership, mentorship, and governance across Databricks, Airflow, SQL, PySpark, and related infrastructure, with a remote-friendly setup within the

Qualifications

• 8+ years of professional experience in data engineering, data architecture, big data development, ETL engineering, or related roles.
• 3+ years of managerial experience leading data engineers or technical teams in a hands-on capacity.
• Strong hands-on expertise with SQL, PySpark, Databricks, and Airflow or equivalent tooling.
• Experience building and scaling production data pipelines, datasets, and data delivery systems.
• Experience collaborating with product, research, and operations teams to deliver reliable data products.

Responsibilities

• Lead, coach, and develop a global data engineering team while remaining close to architecture and delivery.
• Partner with Technical PMs to translate roadmaps into scalable technical plans.
• Build and improve scalable data pipelines, data models, and QA systems for multiple data products.
• Collaborate with stakeholders to ensure reliable delivery and continuous improvement of data platforms.
• Leverage AI coding tools to accelerate development, QA, and documentation.

Skills

SQL

PySpark

Databricks

Airflow

AI tooling

Tools

Databricks

Airflow

SQL

PySpark

Job description

YipitData is seeking a Senior Data Engineering Manager to lead a global data engineering team responsible for large-scale data pipelines and production datasets. You’ll own data architecture, guide implementation, and collaborate with product and research teams to deliver reliable data assets and AI-ready datasets.

This role emphasizes hands-on leadership, mentorship, and governance across Databricks, Airflow, SQL, PySpark, and related infrastructure, with a remote-friendly setup within the