Lead Platform & Data Infrastructure Engineer

Minga•Vancouver, BC

52d•$130,000 - $150,000•Hybrid

About The Position

At Minga, we’re creating the Student Behavior Platform schools can’t imagine running without. We’re on a mission to make school life run smoother and have fun while we’re at it. We’re a tight-knit team of curious, creative, and low-ego humans who genuinely enjoy working together. We care deeply about the work we do and the people we do it with, and that shows up in how we lead, collaborate, and celebrate. Our culture is built on trust, ownership, and continuous learning. Whether you’re working from our Kelowna HQ or remotely, you’ll have the autonomy to do your best work, the support to grow, and the opportunity to make a real impact in the lives of educators and students. The Role We’re not just hiring for a position, we’re adding a teammate. We are looking for a Lead Platform & Data Infrastructure Engineer to own and evolve the systems that power both our product runtime and our analytics ecosystem. This is a senior, systems-level role for someone who thinks in platforms, not just services. Minga is scaling its product, its infrastructure, and its data capabilities. Today, our systems support current growth. But as we scale users, data volume, and engineering headcount, we need stronger foundations across: Infrastructure reliability Developer platform tooling Database scalability Data pipelines and analytics architecture A Lead Platform & Data Infrastructure Engineer Anticipates scale constraints before they become outages. Designs systems that engineers don’t need to think about. Balances runtime reliability with data scalability. Improves velocity by reducing operational drag. Makes architectural decisions that hold up under 5–10x growth.

Requirements

7+ years in backend, infrastructure, or platform engineering.
Strong production experience with Kubernetes.
Experience operating systems on GCP (or similar cloud provider).
Experience building or maintaining data pipelines and warehouse integrations.
Strong understanding of database scaling, connection management, and replication.
Experience with CI/CD systems and infrastructure-as-code.
Familiarity with containerized environments (Docker).
Strong debugging skills in distributed systems.
Clear written and verbal communication skills.

Nice To Haves

Experience designing multi-tenant SaaS systems.
Experience with streaming/event-driven architectures.
Experience with data warehouse platforms (e.g., BigQuery, Snowflake, Redshift).
Experience improving OLTP-to-OLAP separation.
Familiarity with observability tooling (Honeycomb, Datadog, OpenTelemetry).
Experience supporting analytics or BI teams.

Responsibilities

Lead evolution of our Kubernetes-based infrastructure.
Improve resilience, scalability, and fault isolation.
Strengthen networking, database connection strategies, and service reliability.
Reduce production risk through proactive reliability engineering.
Design and implement reliable data pipelines from product systems to our data warehouse.
Help decouple OLTP workloads from analytics workloads.
Improve data reliability, monitoring, and lineage.
Collaborate with product and analytics stakeholders to support reporting needs.
Ensure data systems scale with customer growth and usage patterns.
Improve CI/CD reliability and deployment confidence.
Simplify local and ephemeral development environments.
Build repeatable infrastructure patterns via infrastructure-as-code.
Reduce friction for engineers shipping features.
Improve logging, metrics, tracing, and system visibility.
Define SLIs/SLOs for both product runtime and data systems.
Lead technical post-incident reviews and systemic improvements.
Establish clarity in operational health reporting.