Engineering Manager, Data Platform & Infra Lead

MNTN; Austin (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

MNTN is seeking an Engineering Manager to lead the Data Platform team, partnering with a Staff Engineer to define roadmaps and deliver high-leverage tooling. This hands-on leadership role emphasizes technical excellence, code contribution, and growing a skilled engineering team.

You will collaborate across data science, analytics, product, and engineering to enable scalable data workflows, maintain governance, and improve observability. Join a growth-focused, people-first culture.

Qualifications

• 7+ years of software engineering experience with leadership experience.
• Experience building internal platforms or developer tools, data-intensive environments.
• Proficiency with modern data infra: orchestration, warehousing, streaming, and transformation tools.

Responsibilities

• Lead the Data Platform team in designing, building, and maintaining core infrastructure and tooling.
• Partner with the Principal Engineer to define the team’s technical roadmap and architecture.
• Collaborate with data science, analytics, product, and engineering teams to shape platform features.
• Ensure high reliability, scalability, and governance of data pipelines and infra.
• Establish best practices for data engineering and platform development.
• Provide hands-on technical leadership and contribute code as needed.
• Hire and coach engineers to grow a high-performing team.
• Communicate platform roadmap and priorities to stakeholders.

Skills

Senior software eng

Team leadership

Data platform

Cross-functional

Hands-on leadership

Tools

Airflow

Dagster

BigQuery

Snowflake

Kafka

SQLMesh

AWS

GCP

Job description

MNTN is seeking an Engineering Manager to lead the Data Platform team, partnering with a Staff Engineer to define roadmaps and deliver high-leverage tooling. This hands-on leadership role emphasizes technical excellence, code contribution, and growing a skilled engineering team.

You will collaborate across data science, analytics, product, and engineering to enable scalable data workflows, maintain governance, and improve observability. Join a growth-focused, people-first culture.