Intermediate DataOps/Cloud Data Engineer

Akkodis group; Toronto; Remote; CAD 80,000 - 110,000; Full time

Job summary

Akkodis group is looking for an Intermediate DataOps/Cloud Data Engineer in Toronto to enhance advanced analytics and cloud infrastructure. The ideal candidate will have over 5 years of experience in data engineering, particularly with Azure services, and will contribute to optimizing data solutions and ensuring data quality across diverse projects.

Qualifications

• 5+ years of experience in data engineering and data modeling.
• Deep expertise with Azure services including Azure SQL, Synapse Analytics, Data Lake.
• Strong background in data pipeline development using ADF, Databricks, Azure DevOps.

Responsibilities

• Build and maintain scalable, high-performance data pipelines.
• Optimize data workflows for reliability and low latency.
• Collaborate with stakeholders to translate requirements into data solutions.

Skills

Data engineering

Azure SQL

Databricks

Data pipelines

Azure Data Factory

Job description

The Client is seeking an Intermediate DataOps/Cloud Data Engineer to design and optimize data solutions supporting advanced analytics and cloud data initiatives. This role is ideal for a skilled engineer with hands-on experience in Azure-based data services and automation.

Job Title: Intermediate DataOps/Cloud Data Engineer

Job Location: Toronto, ON/Remote

Job Description

Must Haves:

· 5+ years of experience in data engineering and data modeling

· Deep expertise with Azure services: Azure SQL, Synapse Analytics, Data Lake, Storage, Databricks

· Strong background in data pipeline development using ADF, Databricks, Azure DevOps, or GitHub Actions

Key Responsibilities:

· Build and maintain scalable, high-performance data pipelines with Azure Data Factory and Databricks

· Optimize data workflows for reliability and low latency

· Ensure data quality and consistency through validation and cleansing techniques

· Collaborate with stakeholders to translate requirements into data solutions

· Troubleshoot data transformation and orchestration issues

· Enable analytics and machine learning through effective data integration

· Contribute to governance efforts ensuring compliance with data privacy and quality standards

· Support complex data migrations including OLTP/OLAP and large-scale datasets to cloud platforms

This is a fantastic opportunity to play a key role in modernizing data infrastructure across government programs.