Data Architect for Large-Scale Data Infrastructure

1 week ago


Toronto, Canada Agilus Work Solutions Full time
Job Description

We are seeking an experienced Data Engineer to join our innovative team at Agilus Work Solutions. This contract role will last 16 months and requires a strong background in designing, optimizing, and maintaining scalable data infrastructure.

The successful candidate will design, optimize, and maintain scalable data infrastructure that supports various data initiatives, including AI and machine learning (ML) capabilities. Key responsibilities include leading data and AI/ML initiatives, overseeing system and database integrations, developing and managing system and database integrations, guiding the development of reports and data analysis tools, collaborating with development teams, automating ETL processes and database operations, performing proactive database maintenance and monitoring, identifying and resolving database issues, participating in the full application lifecycle, conducting peer code reviews, and staying up to date with the latest technologies.

To be successful in this role, you must have a Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field. A minimum of 5 years of data engineering experience is required, with a strong background in metadata management, AI/ML project support, and working with SQL and Python.

Requirements
  • Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • Experience: At least 5 years of data engineering experience with a strong background in metadata management, AI/ML project support, and working with SQL and Python.
Technical Skills
  • Data Analysis & Reporting: Proficiency in data analysis, reporting, and warehousing using tools like SQL Server Reporting Services (SSRS), SQL Server Integration Services (SSIS), and Tableau.
  • Database & Big Data Technologies: Extensive experience with database systems and big data tools, including SQL, NoSQL, Hadoop, Spark, and Kafka, particularly in handling large, complex datasets.
  • Database Technologies: Strong command of relational database technologies, specifically MS SQL Server, MongoDB, AWS Redshift, and PostgreSQL.
  • Performance Optimization: Proven expertise in performance tuning, query optimization, and experience with tools such as Performance Monitor, SQL Profiler, and other monitoring and troubleshooting tools.
Estimated Salary: $120,000 - $150,000 per year

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