Data Engineer

United Software Group Inc.; Toronto; On-site; CAD 80,000 - 120,000; Full time

Job summary

A leading company in the tech sector is seeking a Data Engineer for a 9-month contract in Toronto. The ideal candidate will design and maintain data pipelines and warehousing solutions on Azure, collaborating closely with data scientists and analysts. This role requires strong technical skills in Azure technologies, ADF, Databricks, and Snowflake, aiming to transform raw data into actionable insights for business decisions.

Qualifications

• Proven experience in designing and managing data pipelines using Azure Data Factory.
• Hands-on experience with Databricks and Spark programming.
• Extensive experience with Snowflake for data warehousing.

Responsibilities

• Design, develop, and maintain data pipelines using Azure Data Factory.
• Build and optimize data warehousing solutions on Snowflake.
• Collaborate with data scientists to provide efficient data solutions.

Skills

Azure Cloud

Data Modeling

SQL

Data Quality

Scripting

Education

Microsoft Certified: Azure Data Engineer Associate

Snowflake SnowPro Core Certification

Databricks Certified Associate Developer for Apache Spark

Tools

Azure Data Factory (ADF)

Databricks

Snowflake

Control-M

Git

Job description

Role: Data Engineering – DE

9 Months Contract

Location: Toronto ON – ONSITE

Job Summary

We are seeking a highly motivated and experienced Data Engineer to join our growing data team. As a Data Engineer, you will be responsible for designing, building, and maintaining scalable and reliable data pipelines and data warehousing solutions on the Azure cloud platform. You will work closely with data scientists, analysts, and other stakeholders to transform raw data into valuable insights that drive business decisions. The ideal candidate possesses a strong understanding of data engineering principles, proficiency in Azure cloud technologies, and hands-on experience with ADF, Databricks, Snowflake, and Control-M.

Responsibilities:

Design, develop, and maintain robust and scalable data pipelines using Azure Data Factory (ADF).

Build and optimize data warehousing solutions on Snowflake, ensuring performance, scalability, and data quality.

Leverage Databricks for data processing, transformation, and advanced analytics using Spark and Python/Scala.

Implement and manage data orchestration and scheduling using Control-M.

Collaborate with data scientists and analysts to understand their data requirements and provide efficient data solutions.

Monitor and troubleshoot data pipelines and data warehouse performance, ensuring data integrity and reliability.

Implement data quality checks and validation processes to ensure accuracy and consistency of data.

Develop and maintain data models and schemas for optimal data storage and retrieval.

Implement and maintain data security and governance policies.

Stay up-to-date with the latest advancements in Azure cloud technologies and data engineering best practices.

Document data pipelines, data models, and ETL processes.

Participate in code reviews and contribute to the development of data engineering standards and best practices.

Troubleshoot and resolve data-related issues in a timely manner.

Required Technical Skills:

Azure Cloud: Deep understanding of Azure cloud services, particularly in the data and analytics domain.

Azure Data Factory (ADF): Proven experience in designing, building, deploying, and managing complex data pipelines using ADF, including data flows and mapping data flows.

Databricks: Hands-on experience with Databricks, including Spark programming (Python or Scala), Delta Lake, and optimizing Spark jobs for performance.

Snowflake: Extensive experience in designing, developing, and administering data warehouses on Snowflake, including data modeling, SQL development, performance tuning, and security features.

Control-M: Experience in using Control-M for workflow orchestration, scheduling, monitoring, and managing batch processes.

SQL: Strong proficiency in SQL for data querying, manipulation, and analysis across different database systems.

Data Modeling: Solid understanding of different data modeling techniques (e.g., relational, dimensional).

ETL/ELT Concepts: Comprehensive understanding of ETL and ELT principles and best practices.

Scripting: Proficiency in at least one scripting language such as Python for automation and data manipulation.

Version Control: Experience with Git and related version control workflows.

Data Quality: Understanding of data quality principles and experience implementing data quality checks and processes.

Desired Technical Skills:

Experience with other Azure data services such as Azure Synapse Analytics, Azure Data Lake Storage (ADLS), Azure Event Hubs, and Azure Functions.

Knowledge of data governance frameworks and tools.

Experience with CI/CD pipelines for data engineering deployments.

Familiarity with agile development methodologies.

Knowledge of NoSQL databases.

Technical Certifications (Preferred):

Microsoft Certified: Azure Data Engineer Associate

Snowflake SnowPro Core Certification

Databricks Certified Associate Developer for Apache Spark

Control-M certification