Full-Time

Tech Lead / Solution Architect

ShyftLabs

ShyftLabs

11-50 employees

Data-driven decision-making platform for organizations

Compensation Overview

CA$130k - CA$170k/yr

Toronto, ON, Canada

Hybrid

Three days per week on-site in Toronto.

Category
Sales & Solution Engineering
Software Engineering
Required Skills
Microsoft Azure
Python
Node.js
BigQuery
SQL
Apache Kafka
Computer Networking
Java
ClickHouse
.NET
AWS
DevOps
Databricks
Snowflake
Google Cloud Platform

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Requirements
  • 7+ years of software/data engineering experience, including 3+ years in a tech lead, solution architect, or delivery lead role.
  • Cloud-agnostic experience, production-grade design and delivery across at least two of GCP, AWS, and Azure, including networking, identity, compute, managed data services, and CI/CD.
  • Strong data engineering, SQL fluency (window functions, CTEs, hierarchical queries), experience with one or more of BigQuery, Databricks, Snowflake, or ClickHouse, and familiarity with batch and streaming pipelines (Kafka or equivalent).
  • Comfort across multiple application stacks (e.g., Node.js, Python, Java, .NET), you don't need to be expert in all of them, but you should be able to read code and reason about design in more than one.
  • Track record of leading client-facing delivery: scoping, estimation, resource and budget planning, and stakeholder communication.
  • Experience leading architecture review and enterprise governance forums (ARB, InfoSec, security/compliance).
  • Excellent written communication, concise, warm, and professional. Comfortable drafting status updates, scoping docs, and architecture decisions for mixed technical and business audiences.
  • A startup mindset: adaptable, execution-focused, comfortable owning ambiguity end-to-end.
Responsibilities
  • Design end-to-end solutions spanning data pipelines, application services, and cloud infrastructure across major public clouds (GCP, AWS, Azure).
  • Make architecture decisions on data warehousing (BigQuery, Databricks, Snowflake, ClickHouse), event/streaming layers (Kafka), API design, and cloud networking (DNS, CDN, WAF, identity, load balancing).
  • Lead architecture review and enterprise governance processes.
  • Produce architecture diagrams, data flow diagrams, integration specs, and decision records that engineering and client teams can actually use.
  • Own technical delivery for client engagements: scoping, estimation, resource planning, risk tracking, and milestone management.
  • Build and maintain capacity plans and budget models across development, onboarding, and support streams; surface tradeoffs clearly to leadership and clients.
  • Translate ambiguous business asks into structured workstreams with clear ownership and dependencies.
  • Write production-quality code and SQL when needed, this role is not purely advisory. Expect to debug a BigQuery or Databricks query, fix a CI pipeline, set up cloud networking, or unblock a deployment.
  • Run proofs of concept to validate architectural approaches, including AI/LLM integrations, RAG patterns, and data pipeline designs, before committing the team.
  • Review code, designs, and infrastructure changes; set the bar for engineering quality.
  • Act as a senior technical voice in client meetings, explaining decisions, defending tradeoffs, and pushing back constructively when scope or assumptions need to change.
  • Coordinate with external vendors, consultants, and client-side engineering, product, and security teams.
  • Communicate concisely in writing and on calls; tailor depth and tone to the audience.
  • Guide engineers through architectural decisions and design reviews.
  • Coordinate across globally distributed teams and time zones (Toronto, India).
  • Champion best practices around code quality, testing, observability, and documentation.
Desired Qualifications
  • Experience designing high-throughput, low-latency distributed systems, real-time analytics, event-driven platforms, or high-traffic API/microservice architectures.
  • Hands-on experience with AI/LLM integrations, RAG systems, or agentic/MCP-style architectures in production.
  • Familiarity with Microsoft data stack (SQL Server, Azure SQL, Azure DevOps) alongside modern lakehouse tools.
  • Prior experience working with Fortune 500 enterprise clients in a consulting or product-services model.

ShyftLabs helps organizations adopt a data-first approach to decision making by designing and implementing processes that turn data into actionable insights. Its solution builds structured analytics workflows and governance, so teams access trustworthy data, follow defined steps, and act on results with clarity. Unlike tools that only show dashboards, ShyftLabs focuses on repeatable data practices and governance that speed up decisions and reduce ad hoc analysis. The goal is to help organizations stay ahead of the competition by enabling faster, more informed decisions across the business.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

Canada

Founded

2018

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See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Toronto Port Authority launched Carter-powered DOOH at Billy Bishop on 2026-04-13.
  • ShyftLabs opened a new office in August 2025, signaling expansion.
  • Its 250-person team and zero funding create profitable growth discipline.

What critics are saying

  • ShyftLabs remains unfunded, limiting hiring, acquisitions, and product investment.
  • Carter faces entrenched rivals like Adobe, Google, and public adtech platforms.
  • A consulting-heavy model makes revenue vulnerable if airport and enterprise deals stall.

What makes ShyftLabs unique

  • ShyftLabs bootstrapped to 250 employees without outside capital.
  • Its Carter platform combines AI, programmatic activation, and measurable DOOH optimization.
  • Toronto and Hyderabad delivery centers support enterprise data and AdTech work.

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Benefits

Health Insurance

Hybrid Work Options

Professional Development Budget