Remote Data Engineering Lead: Scalable Pipelines

Ladders; United States; Remote; USD 120,000 - 194,000; Full time

Benefits offered by this job

Laptop and monitors provided

Monthly connectivity reimbursement

Dedicated workspace support

Continuous learning opportunities

Job summary

Ladders is seeking a Managing Engineer, Data Engineering to lead a team building scalable data platforms and solutions that power decision-making.

You will set engineering standards, mentor engineers, and partner with cross-functional stakeholders to improve reliability, security, and performance across data pipelines, while balancing hands-on technical leadership with production support and governance.

Qualifications

• 5–7 years of experience building data solutions and enterprise software systems.
• 1–3 years of technical leadership or mentoring experience.
• Strong hands-on data pipeline development in Python/Java/Scala.
• Experience with Spark and Kafka.
• Proficiency in SQL/NoSQL databases and data modeling.
• Familiarity with Docker and Kubernetes.
• Strong communication and stakeholder management skills.

Responsibilities

• Lead and mentor Data Engineers, supporting professional growth and technical development
• Establish engineering standards and promote best practices across the team
• Design and implement scalable batch and streaming data solutions
• Integrate data from multiple sources while ensuring reliability and security
• Optimize data pipelines and support production operations during incidents
• Collaborate with cross‑functional teams to align on data priorities
• Promote data governance and ensure compliance with security standards

Skills

Python

Java

Scala

Data pipeline development

Communication

Stakeholder management

Tools

Apache Spark

Kafka

Docker

Kubernetes

SQL

NoSQL databases

Data modeling

Job description

Ladders is seeking a Managing Engineer, Data Engineering to lead a team building scalable data platforms and solutions that power decision-making.

You will set engineering standards, mentor engineers, and partner with cross-functional stakeholders to improve reliability, security, and performance across data pipelines, while balancing hands-on technical leadership with production support and governance.