Senior Data Engineering Developer II

Design, develop, and maintain highly scalable, robust, and fault-tolerant data processing systems.,Lead and manage data engineering projects with minimal supervision, assessing impact on existing infrastructure and implementing new data structures.,Design and deploy AI-driven data transformation processes and intelligent data quality frameworks.,Develop and implement AI-powered metadata management and data cataloging systems for data discovery, lineage tracking, and semantic understanding.,Engineer sophisticated data solutions, including feature stores and optimized data access layers for AI/ML models.,Utilize machine learning models to optimize large-scale data storage solutions, incorporating AI-driven data lifecycle management and predictive tiering.,Implement intelligent monitoring and alerting systems leveraging AI/ML for predictive failure detection and anomaly identification.,Contribute to the strategic design and evolution of data architectures, advocating for AI-driven optimizations.,Enhance CI/CD pipelines for data infrastructure and applications through AI-driven testing and automated code review.,Design, develop, and champion the adoption of novel AI-powered tools and frameworks to automate and revolutionize data engineering tasks.

Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a similar technical field, or equivalent extensive professional experience.,5-7 years within senior data engineering or closely related data-focused roles.,Proficient in database technologies, including database processing and performance tuning.,Strong experience designing efficient data models and understanding Data Warehouse design patterns for maximum scalability.,Advanced skills in transforming raw data into curated, actionable data elements.,Substantial hands-on experience leveraging cloud-native data services within major cloud environments, specifically Google Cloud Platform (GCP) services (BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub).,Practical, demonstrable experience in implementing and managing data warehousing solutions, applying dimensional modeling techniques (e.g., Star Schema, Snowflake Schema), and designing effective data marts.,Exceptional analytical acumen and sophisticated problem-solving capabilities, with a commitment to data accuracy and attention to detail.,Prior successful experience working within dynamic Agile or Scrum development methodologies.,Practical familiarity with MLOps principles, practices, and associated tooling.,Strong understanding of data streaming paradigms and experience implementing real-time data processing architectures using technologies like Kafka Streams.,Proven experience in performance optimization and strategic cost management for cloud-based big data and data processing solutions.,Excellent interpersonal, written, and verbal communication skills.,Demonstrated ability to effectively process, manage, and integrate data residing in various formats (structured, semi-structured, potentially unstructured).,Experience in architecting and implementing intelligent, adaptive data pipelines leveraging AI/ML techniques.,Prior experience in partnering with AI/ML specialists to co-design and implement robust data infrastructure, feature stores, and model deployment pipelines.

Bachelor's Degree

Must be based in Canada and report to a set Bell office for a minimum of 3 days a week (for Hybrid work arrangement).