Data Architect

6 days ago


Toronto, Ontario, Canada SADA Full time
About SADA

SADA is a leading provider of cloud-based solutions, dedicated to helping businesses thrive in the digital age. Our team of experts is passionate about delivering innovative, scalable, and secure solutions that meet the evolving needs of our clients.

Job Summary

We are seeking a highly skilled Data Engineer to join our accomplished Data Engineering Team. As a Data Engineer at SADA, you will play a critical role in designing, building, and maintaining advanced data infrastructures on Google Cloud Platform (GCP). Your expertise will be instrumental in addressing real-world data challenges for a broad range of clients, from startups to industry pioneers.

Key Responsibilities
  • Innovate and Solve Complex Problems: Design and build advanced software systems to efficiently process petabytes of data.
  • Implement Best Practices: Quickly adapt and utilize the latest software engineering practices.
  • Collaborate Effectively: Work alongside engineers, project managers, and solutions architects to deliver new products and features.
  • Develop Data Pipelines: Design, implement, and maintain big data pipelines that drive critical business decisions.
  • Maintain Quality: Ensure that all software you create is testable and thoroughly tested.
  • Participate in Design Discussions: Actively contribute to architecture, design, and implementation discussions.
  • Drive Project Success: Participate in planning, execution, and successful delivery of complex technical projects.
  • Engage with Clients: Take part in technical discussions, translating technical concepts into clear, actionable strategies that align with their business objectives.
Requirements
  • Google Professional Data Engineer Certified: Must be certified or able to complete within the first 45 days of employment.
  • Expertise in at least one of the following domain areas:
    • Big Data: Managing Hadoop clusters, troubleshooting, migrating Hadoop workloads, architecting solutions, ETL pipelines with Spark, Apache Beam, messaging systems like Pub/Sub, Kafka.
    • Data Warehousing: Building data warehouse solutions, schema designs, ETL/ELT pipelines, reporting tools.
    • Data Migration: Migrating data stores to scalable cloud-based stores with minimal downtime.
    • Backup and Disaster Recovery: Building large-scale production-grade data backup, restore, and disaster recovery solutions.
    • Software Development: Experience writing software in Python, Java, Scala, or Go.
    • Production-Grade Data Solutions: Experience with relational and NoSQL data solutions.
    • System Monitoring and Performance Tuning: Experience in systems monitoring, capacity planning, and performance tuning.
    • Technical Consulting: Experience in technical consulting or other customer-facing roles.
  • Preferred Qualifications:
    • Google Cloud Data Products: Experience with CloudSQL, Spanner, Cloud Storage, Pub/Sub, Dataflow, Dataproc, Bigtable, BigQuery, Dataprep, Composer.
    • IoT Architectures: Experience building real-time data streaming pipelines.
    • Machine Learning: Applied experience operationalizing machine learning models on large datasets.
    • Industry Trends: Knowledge of industry trends and new technologies, and the ability to apply these to architectural needs.
    • Leadership and Self-Direction: Demonstrated leadership skills and the ability to teach others.
    • Statistical Tools: Proficiency in selecting the right statistical tools for data analysis problems.

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