Business Analyst working with the University of Alberta's Asset Management platform and ensuring effective lifecycle management. Collaborating with various departments for data integrity and process optimization.
About the role
- Data Engineer designing and optimizing scalable data pipelines and cloud architectures at Hartford. Collaborating with analytics and AI teams for data quality and feature deployment.
Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes for structured and unstructured data
- Build and optimize cloud-based data architectures, data lakes, and data warehouses (preference for GCP)
- Ingest data from diverse sources including APIs, databases, streaming platforms, and third-party systems
- Ensure data quality, reliability, performance, and scalability across data platforms
- Optimize data models for analytics, reporting, and machine learning use cases
- Collaborate with analytics, data science, and AI teams to support feature engineering and model deployment
- Implement monitoring, logging, and alerting to ensure pipeline health and performance
- Apply best practices for security, data governance, privacy, and access controls
- Document data pipelines, schemas, and architectural decisions to promote transparency and reusability
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent experience)
- Strong programming experience in SQL and at least one of Python, Java, or Scala
- Experience designing and building data pipelines and data platforms in a cloud environment
- Solid understanding of data warehousing concepts, dimensional modeling, and data optimization
- Experience working with large datasets and distributed data processing frameworks
- Familiarity with CI/CD, version control (Git), and infrastructure-as-code concepts
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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