Data Architect (Mississauga)
Tredence
About Us
Tredence differentiates itself from other analytics services firms by enabling last‑mile adoption of insights. We drive true business impact by uniting our strengths in business analytics, data science, and software engineering. We help our clients deliver on the artificial intelligence imperative in a practical and demystified way.
Job Overview
As a Specialist Data Engineer at Tredence, you will play a pivotal role in designing, building, and optimizing data pipelines and analytics solutions on Google Cloud Platform (GCP) tailored for the retail sector. Success in this role means enabling seamless data integration and transformation that drives insightful decision‑making and business value for our clients. You will collaborate closely with cross‑functional teams to ensure reliable data infrastructure that supports scalable analytics and AI initiatives.
Responsibilities
- Data Pipelines: Design, develop, and maintain workflows using GCP Composer and other GCP services.
- Data Storage: Architect scalable solutions leveraging BigQuery, BigTable, and Datastore tailored to retail data requirements.
- Data Processing: Develop and optimize frameworks using DataFlow and DataProc, ensuring high‑quality ingestion and transformation.
- Collaboration: Work with data scientists, analysts, and engineers to integrate solutions supporting advanced analytics.
- DevOps: Manage and automate deployment pipelines for consistent system performance.
- Troubleshooting: Analyze and resolve data engineering issues, proactively improving reliability.
- Governance: Document processes, maintain standards, and ensure compliance with organizational and client policies.
Qualifications
- 10–15 years of professional experience in data engineering with a strong focus on GCP.
- Expert‑level knowledge in GCP Composer, BigQuery, BigTable, DataFlow, DataProc, Datastore, and DevOps tooling.
- Advanced programming skills in Python and proficiency in SQL.
- Bachelor’s degree in Computer Science, Engineering, IT, or a related field.
- Strong problem‑solving abilities and excellent communication skills.
- Experience working in retail data environments or a comparable data‑intensive domain.
Good to Have Skills
- GCP certifications (Google Certified Data Engineer, Google Cloud DevOps Engineer).
- Familiarity with Docker and Kubernetes.
- Experience with Java or Scala for data workloads.
- Knowledge of machine‑learning workflows and pipeline integration.
- Exposure to agile methodologies and cloud security best practices.
Benefits
- Work on cutting‑edge retail analytics projects.
- Hybrid work model supporting work‑life balance.
- Grow your expertise in Google Cloud while contributing to impactful AI‑driven solutions.
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