Lead Data Architect for Scalable Infrastructure

7 days ago

Toronto, Canada Agilus Work Solutions Full time

As a seasoned Data Engineer at Agilus Work Solutions, you will play a pivotal role in designing and optimizing scalable data infrastructure to support various data initiatives, including AI and machine learning (ML) capabilities. Your expertise will be instrumental in building and maintaining large-scale data pipelines that handle complex datasets for AI/ML models and analytics solutions.

This is an excellent opportunity to leverage your skills in database integration, system optimization, and data analysis to drive business growth and innovation. Reporting directly to the Vice President of IT, you will collaborate with cross-functional teams to deliver cutting-edge solutions that meet our clients' evolving needs.

Key Responsibilities:

  • Data Pipeline Development: Design, optimize, and maintain large-scale data pipelines using SQL and Python to ensure seamless integration, testing, and deployment.
  • Database Integration: Oversee system and database integrations to facilitate scalable data flows and interoperability between platforms and applications.
  • Data Analysis and Insights: Develop and manage system and database integrations to provide timely, accurate insights for business decision-making.
  • Collaboration and Teamwork: Collaborate with development teams on data modeling, database schema design, SQL query optimization, and the application of complex business rules.
  • Automation and Monitoring: Automate ETL processes and database operations by writing stored procedures and scripts to enhance efficiency and reliability of data workflows.
  • Proactive Database Maintenance: Perform proactive database maintenance and monitoring using modern tools like Datadog and New Relic to ensure high availability, scalability, and performance.
  • Problem-Solving and Troubleshooting: Identify, troubleshoot, and resolve database issues in production environments and during solution deployment to minimize disruption to business operations.
  • Cloud-Based Development: Participate in the full application lifecycle, from technical design to cloud-based development, testing, and deployment using platforms like AWS and Azure.
  • Quality Assurance and Code Reviews: Conduct peer code reviews and ensure adherence to best practices in software development and database management for quality and security.
  • Professional Development: Stay up-to-date with the latest technologies in AI/ML, cloud computing, and data engineering to continuously enhance system capabilities and drive innovation.

Requirements:

  • Educational Background: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • Experience: At least 5 years of experience in data engineering 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.

Bonus Skills:

Experience with MuleSoft, Salesforce, and API integrations is a plus. To be considered for this opportunity, you must have Canadian citizenship, be a permanent resident, or have an active work permit that covers the entire length of the contract. You must also reside in the GTA to comply with our hybrid work schedule, which requires regular in-person days in the office. The estimated salary for this position is $120,000 - $150,000 per year, based on industry standards and location.

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