Lektik is an AI engineering and venture studio that builds intelligent software platforms for enterprises across healthcare, logistics, manufacturing, supply chain, finance, public sector, and emerging technology companies.

We don't build demos.

We build production systems that solve real business problems.

Our work spans AI agents, enterprise orchestration, semantic knowledge graphs, Retrieval Augmented Generation (RAG), workflow automation, decision intelligence, and enterprise data platforms.

Our platforms connect fragmented enterprise systems—including ERP, CRM, finance, HR, operations, documents, and custom applications—into unified business intelligence that people can query naturally.

Every implementation expands our reusable platform, making future deployments faster, smarter, and more valuable.

Our engineering team works on products that are deployed, revenue-generating, and solving problems for real clients across multiple industries.

If you enjoy building systems that combine data engineering, AI, cloud infrastructure, and enterprise architecture, you'll fit right in.

THE ROLE

As a Data Engineer at Lektik, you'll own the data foundation that powers our AI platforms.

You'll design, build, and operate reliable data pipelines connecting dozens of enterprise systems into modern cloud data platforms.

Your work enables

AI Agents

Enterprise Search

Knowledge Graphs

RAG Applications

Executive Dashboards

Decision Intelligence Platforms

Business Analytics

Machine Learning pipelines

You'll work closely with software engineers, AI engineers, architects, and solution consultants to ensure data is accurate, trusted, scalable, and available in real time.

This is a product-building role—not a maintenance role.

You'll help shape the architecture that powers next-generation enterprise AI solutions.

WHAT YOU'LL DO

Build scalable ETL/ELT pipelines integrating ERP, CRM, HRMS, Finance, Manufacturing,



Logistics, IoT, APIs, databases, and cloud platforms.

Design and maintain enterprise data warehouses using Snowflake, Microsoft Fabric, Azure SQL, PostgreSQL, SQL Server, or similar technologies.

Build robust data transformation pipelines using dbt, SQL, Python, Spark, or equivalent tools.

Design semantic data models that power enterprise AI and natural language querying.

Build data pipelines supporting RAG systems, vector databases, and AI knowledge platforms.

Develop data quality frameworks, validation rules, monitoring, alerting, lineage, and governance.

Build scalable ingestion pipelines from structured, semi-structured, and unstructured data sources.

Collaborate with AI engineers to prepare datasets for LLMs, machine learning, and intelligent agents.

Optimize warehouse performance, query efficiency, storage costs, and pipeline reliability.

Work closely with product teams to ensure new applications emit high-quality event and operational data.

Contribute to reusable enterprise data platform components that accelerate future client implementations.

WHAT WE'RE LOOKING FOR

Required

Robust SQL with experience writing complex analytical queries.

Strong Python for data engineering.

Experience building production-grade ETL/ELT pipelines.

Experience with cloud data warehouses such as Snowflake, Microsoft Fabric, BigQuery, Redshift, Synapse, or Databricks.

Experience with dbt or equivalent transformation frameworks.

Experience integrating SaaS platforms using APIs.





Experience with Azure and/or AWS cloud platforms.

Good understanding of data modeling (star schema, dimensional modeling, normalization).

Experience with orchestration tools such as Airflow, Prefect, Azure Data Factory, Dagster, or similar.

Experience with Git and CI/CD practices.

Strong debugging and problem-solving skills.

Excellent written and verbal communication skills.

Nice to Have

Experience with enterprise knowledge graphs or semantic data models.

Experience with vector databases and Retrieval Augmented Generation (RAG).

Experience working with LLMs and AI applications.

Experience with Microsoft Fabric.

Experience with Apache Spark.

Experience with Kafka or event-driven architectures.

Experience with Graph databases (Neo4j, Memgraph).

Experience with OpenSearch or Elasticsearch.

Experience with enterprise integration platforms.

Experience working on supply chain, healthcare, finance, or manufacturing solutions.

OUR TECHNOLOGY STACK

You don't need experience with everything, but you'll likely work with technologies such as:

Python

SQL

Snowflake

Microsoft Fabric

PostgreSQL

SQL Server

Azure

AWS dbt

Airflow

Azure Data Factory

Spark

OpenSearch

Neo4j

Kafka

Azure OpenAI

OpenAI

Claude

GitHub Actions

Docker

Kubernetes

WHY YOU'LL LOVE IT HERE

At Lektik, you'll work on challenging enterprise AI projects that move beyond chatbots and prototypes.

You'll help build platforms that organizations rely on to make critical business decisions.

You'll collaborate with experienced architects, AI engineers, product teams, and enterprise clients while contributing to reusable technology that powers multiple products and industries.

- We value ownership, engineering excellence, curiosity, continuous learning, and building technology that creates measurable business impact.

Compensation: Competitive + Performance Bonus

📌 Data Engineer (Canada)
🏢 Lektik
📍 Canada