Data Engineer
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Key skills for this role
About the Role
Scotiabank is looking for a Data Engineer to design, build, and maintain scalable data pipelines within the Enterprise Data & AI Technology organization. You will leverage cloud platforms like Azure and Databricks to process large datasets.
Key Skills for This Role
Responsibilities
- Design, build, and maintain scalable, resilient data pipelines to support ingestion, processing, and distribution of large datasets
- Leverage SaaS platforms and tools to develop, configure, and automate data workflows
- Partner with stakeholders and product managers to gather requirements and onboard new data sources into the cloud data platform
- Implement observability capabilities and continuously optimize application services and pipeline performance
- Perform data integrity validation to ensure accuracy, reliability, and consistency of data
Requirements
- 4+ years of experience working with Data Warehouse / Data Platforms
- 4+ years of experience creating ELT / ETL data pipelines with structured, semi structured, and unstructured data
- 4+ years of experience with CI/CD and source control systems (GitHub, Bitbucket, Terraform)
- 4+ years of experience in Cloud: Azure
- 4+ years of experience in Lakehouse: Databricks
- Experience building data pipelines using Azure Data Factory and ADLS
- Strong programming and scripting skills (SQL, Python, Java, Scala)
- Strong knowledge of cloud infrastructure and microservices architecture
- Experience collaborating with DevOps, Scrum, and Product Teams
- Solid communication skills and ability to translate complex technical problems to business language
Full Job Posting
Role Overview
- The Data Engineer plays a critical role within the Enterprise Data & AI Technology organization
- This organization drives data enabled decision making, AI innovation, and technology modernization across the Bank
In this role, you will:
- Design, build, and maintain scalable, resilient data pipelines to support the ingestion, processing, and distribution of large datasets
- Leverage SaaS platforms and tools to develop, configure, and automate data workflows, improving efficiency across the data engineering lifecycle
- Partner with stakeholders and product managers to gather requirements, design ingestion patterns, and onboard new data sources into the cloud data platform
- Implement observability capabilities and continuously optimize application services and pipeline performance
- Perform data integrity validation to ensure accuracy, reliability, and consistency of data
Do you have the skills?
- Experience building data pipelines and composable cloud based data platforms (Azure), using Azure Data Factory, ADLS
- Experience working with Lakehouse platforms: Databricks, Unity Catalog, Auto Loader
- Experience with data engineering, programming, ETL and ELT processes for data extraction and processing
- Experience working with structured, semi structured, and unstructured data
- Strong programming and scripting skills (SQL, Python, Java, Scala)
- Strong knowledge of cloud infrastructure and microservices architecture
- Experience in creating technical design documentations, both logical and physical view
- Experience collaborating and working with DevOps, Scrum, and Product Teams
- Demonstrated team player with strong communication skills
- Solid communication skills – ability to translate complex technical problems to business language
- Expert at problem solving and debugging
- 4+ years of experience working with Data Warehouse / Data Platforms
What's in it for you?
- Diversity, Equity, Inclusion & Allyship
- Accessibility and Workplace Accommodations
- Upskilling through online courses, cross functional development opportunities, and tuition assistance
- Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits
- Dynamic Ecosystem Free tea & coffee, universal washrooms, and lots of space for team collaboration
- Community Engagement opportunities
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