Data Engineer - Spade

Manitoba, Canada (preferred) but all locations considered.

Job Type

Requirements

Company: Spade Technologies, Inc.

Job Schedule: Full time

Job Location: Manitoba, Canada (preferred) but all locations considered.

Reports To: CTO

Salary Range: $150k-210k CAD

About Spade

Spade is building the data infrastructure that powers the future of food. We connect and unify

herd, feed, financial, processor, and environmental data across the dairy ecosystem—turning

fragmented information into secure, actionable intelligence for farmers, lenders, processors,

and enterprise partners.

Our vision is simple: give every stakeholder in food and agriculture the clarity and

confidence to make better decisions, faster.

To accelerate our delivery timeline, we’re hiring a Data Engineer who thrives in ambiguity,

moves quickly, and can build robust, secure data systems from the ground up.

Role Overview

As a Data Engineer at Spade, you will own the pipelines, data models, and infrastructure that

power our core platform. You’ll design and build reliable ingestion systems for herd, feed, and financial data; ensure data is accurate, performant, secure, and available for internal and external use.

You’ll work closely with backend engineering, product, design, and solutions teams to support both our farmer-facing product and our enterprise customers. This is a foundational role with

tremendous influence over Spade’s architecture and long-term data strategy.

What You’ll Do

• Design, build, and maintain scalable data ingestion pipelines (batch + streaming) for heterogeneous farm and financial data sources.
• Implement ETL/ELT workflows and validation layers.
• Develop unified data models for herd, feed, financial, and operational datasets.
• Manage the complexity of a modern data lake ( Iceberg, Databricks etc )
• Prepare data to be ready for ML workloads, and other AI systems

Data Quality & Observability

• Establish monitoring and alerting for pipeline failures, anomalies and data quality.
• Implement automated data validation, deduplication, and reconciliation.
• Build systems that enforce best practices for governance and lineage.

Security & Compliance

• Work with security/infra teams to enforce Role based access to our multitenant applications.
• Ensure enterprise-grade audit trails and data governance practices.
• Partner with backend engineering to design APIs that expose clean, reliable data.
• Work with PMs and designers to support new product features requiring data access.
• Support Solutions Engineering in onboarding new enterprise customers and integrating their data sources to our system.

Platform Evolution

• Influence architecture decisions and improve systems for performance, scale, and maintainability.
• Help define Spade’s long-term data platform vision and best practices.

What We’re Looking For

Required

• 4+ years of Data Engineering experience in production environments
• Expertise with modern data pipeline tools and technologies (DataBricks, Airflow, DBT, Dagster, Spark, Beam, or similar)
• Experience designing and managing data warehouses or lakehouses
• Hands-on experience with cloud infrastructure (AWS/GCP/Azure)
• Experience with structured and semi-structured data (CSV, JSON, Parquet, Avro)
• Knowledge of data modeling, schema design, and ETL/ELT best practices
• Experience building pipelines that support multiple tenants or customer datasets
• Strong understanding of security, compliance, and data governance
• Ability to thrive in a fast-paced startup environment with shifting priorities

Nice-to-Have

• Background working with financial, agricultural (dairy), IoT, or operational datasets
• Familiarity with event-driven architectures
• Experience contributing to architecture decisions in early-stage startups
• Comfort working across multiple products (farmer-facing + enterprise)

What You’ll Love About Spade

• The opportunity to build foundational systems that transform how food and agriculture operate
• A mission-driven culture focused on real impact—not vanity metrics
• Ownership, autonomy, and the ability to shape the technical direction of the company
• A collaborative, pragmatic team that values impact over ego
• Competitive compensation and meaningful equity