
Data Engineering Lead
1 day ago
We are seeking an experienced Senior Data Architect to lead our team's data engineering efforts. The ideal candidate will have a strong background in designing and implementing large-scale data pipelines, with expertise in building and automating deployments, as well as working with modern DevOps/configuration management tools.
Main Responsibilities:
- Lead the development and maintenance of Continuous Integration/Continuous Deployment (CI/CD) pipelines using GitHub Actions or equivalent tools.
- Configure and maintain GitHub branch protection rules and workflows to ensure smooth code integration and deployment.
- Design and optimize Spark jobs in Databricks for large-scale data processing, ensuring high performance and reliability.
- Automate Databricks deployments using Databricks Asset Bundles (DABs) or similar frameworks.
- Develop robust data pipelines using Python and SQL, focusing on data quality and consistency.
- Implement unit testing, validation, and quality checks for data workflows, ensuring reliability and accuracy.
- Manage multi-environment deployments (Dev, Stage, Prod), ensuring seamless integration and scalability.
- Create and maintain configuration files (YAML, JSON) for workflows, pipelines, and automation, ensuring clarity and efficiency.
- Troubleshoot and resolve configuration or syntax issues in YAML and related files, minimizing downtime.
- Migrate legacy reports into modern, self-serve dashboards (Snowflake, Tableau, Power BI), providing actionable insights.
The successful candidate will partner with cross-functional teams to understand needs and deliver data models, insights, and reporting they can trust, driving business growth and success.
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