Position : GCP Data Engineer
Location : Toronto
Work Model : Hybrid
What is the role
- Design, develop and maintain robust data pipelines for ingestion, transformation, and distribution of large datasets.
- Utilize services and tools to automate data workflows and streamline the data engineering process.
- Collaborate with stakeholders and product managers to analyze, and build data mapping, models and reporting needs.
- Monitor application and pipeline performance.
- Conduct data quality checks
Experience :
- Experience creating ELT data pipelines from scratch
- Experience configuring and using data ingestion tools such as Fivetran, Qlik, Airbyte etc.
- Experience in data modelling, manipulating large data sets and handling raw SQL, and handling other cleaning techniques.
- Experience working with structured, semi-structured, and unstructured data.
- Experience building data pipelines, and composable cloud-based data platforms in AWS, Azure, or GCP.
- Experience collaborating and working with DevOps and Scrum Teams
- Have prior experience with data developer, data engineering, programming, ETL, ELT, processes for data integration.
- Demonstrated team player with strong communication skills and a track record of successful delivery of product development.
- Expert at problem solving.
- Good understanding of continuous integrations and continuous deployment pipeline (CI / CD)
- Strong scripting skills
- Experience working with source control systems such as Github, Bitbucket.
Technical Skills
- 10+ years of experience with Data Warehouse / Data Platforms
- 5+ years of experience creating ELT data pipelines from scratch, working with structured, semi-structured, and unstructured data and SQL.
- 2+ years of experience configuring and using data ingestion tools such as Fivetran, Qlik, Airbyte or others.
- 5+ years of experience with Cloud : GCP
- 5+ years of experience working as a data developer, data engineering, programming, ETL, ELT, processes for data integration.
- 5+ years continuous integrations and continuous deployment pipeline (CI / CD) and working with source control systems such as Github, Bitbucket, and Terraform
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