Lead Data Engineer

VDart Inc; Canada; Remote; CAD 100,000 - 130,000; Full time

Job summary

A leading company seeks a highly skilled Lead Data Engineer with deep expertise in Snowflake, SQL, and Python. This remote role is instrumental in architecting scalable data solutions to support AI, focusing on data pipelines, automation, and governance. Join a team dedicated to driving operational excellence across the data platform.

Qualifications

• 7+ years of experience in data engineering or data platform roles.
• Strong hands-on expertise in Snowflake and advanced Python skills.
• Experience with ETL/ELT pipelines and collaboration with analytics teams.

Responsibilities

• Design, build, and deploy scalable and high-performance data models and pipelines in Snowflake.
• Write efficient and reusable Python scripts to automate Snowflake operations.
• Collaborate on MuleSoft configurations for data ingestion into Snowflake.

Skills

Snowflake

Python

Data Governance

ETL/ELT Pipelines

Tools

MuleSoft

AWS

Azure

GCP

Job description

Lead Data Engineer Snowflake & Python

Fulltime

Remote

Position Overview:

We are seeking a highly skilled Lead Data Engineer with deep expertise in Snowflake , SQL and Python, and exposure to MuleSoft-based integrations. This role will be instrumental in architecting and optimizing scalable data solutions that support AI foundations, data reconciliation, and enterprise-wide automation strategies. You will lead the development of robust Snowflake-based data pipelines, support real-time and batch integrations, and drive operational excellence across the data platform.

Key Responsibilities:

• Design, build, and deploy scalable and high-performance data models and pipelines in Snowflake to support foundational AI/ML, data reconciliation, and automation use cases.
• Develop and optimize complex Snowflake workloads, including ingestion, transformation (Streams, Tasks), and secure data sharing, with a focus on performance and cost efficiency.
• Write efficient and reusable Python scripts to automate Snowflake operations such as data loading, transformation orchestration, and user/role management.
• Support and collaborate on MuleSoft configurations and flows to enable real-time and batch data ingestion into Snowflake using reusable APIs and connectors.
• Diagnose and resolve issues impacting Snowflake data processing, including upstream failures from MuleSoft or other external data sources.
• Maintain secure, compliant Snowflake environments (dev, test, prod) aligned with best practices in data governance and access control.
• Partner with cross-functional teams to define data contracts, integration strategies, and ensure data quality and traceability within Snowflake.
• Continuously evaluate and recommend improvements to Snowflake performance, automation workflows, and MuleSoft-based data integrations.

Required Qualifications:

• 7+ years of experience in data engineering or data platform roles.
• Strong hands-on expertise in Snowflake (data modeling, performance tuning, Streams & Tasks, data sharing).
• Advanced Python skills for scripting, automation, and orchestration.
• Experience with ETL/ELT pipelines and workflow orchestration tools.
• Exposure to MuleSoft or similar iPaaS platforms (e.g., Boomi, Apache Nifi, Talend) for integrating data from enterprise systems.
• Solid understanding of data governance, access control, and environment management in cloud data platforms.
• Experience collaborating with business and analytics teams to define and implement integration strategies.
• Excellent troubleshooting skills and ability to resolve complex data flow issues in distributed environments.

Preferred Qualifications:

• Snowflake certification(s) (e.g., SnowPro Core or Advanced).
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience in building data solutions that support AI/ML or intelligent automation.
• Understanding of API-led integration principles and RESTful API design.