Senior Data Engineer

• Data Infrastructure & Pipelines: Design, develop, and maintain scalable data pipelines using AWS services (e.g., S3, Glue, Lambda, RDS).
• ETL Development: Build robust ETL processes to ingest, transform, and store data efficiently.
• Database & Storage Optimizations: Manage and optimize relational databases to support business needs.
• Data Quality & Governance: Ensure high-quality data through validation, monitoring, and governance best practices.
• Automation & Scripting: Develop scripts and automation tools (Python, SQL, Bash) to streamline data processes and workflows.
• Data Presentation & Accessibility: Support business users by ensuring data is structured and accessible in reporting tools like Tableau or Metabase.
• DevOps & CI/CD: Implement best practices for version control, testing, and deployment of data pipelines (Terraform, GitHub Actions, etc.).
• Collaboration: Work closely with cross-functional teams to translate business requirements into efficient data solutions.

• Proven experience in data engineering, working with cloud-based data platforms (AWS).
• Strong proficiency in Python for data processing and automation.
• Experience with SQL and database management (PostgreSQL, MySQL, or similar).
• Hands-on experience with AWS services such as Glue, S3, Lambda, and RDS.
• Understanding of ETL/ELT best practices and experience building data pipelines.
• Experience with data visualisation and BI tools such as Tableau or Metabase.
• Experience with infrastructure-as-code tools (Terraform, CloudFormation) for data infrastructure automation.
• Strong focus on data quality, security, and governance.

• Familiarity with ML technologies (Sagemaker).
• Experience working in Agile environments and familiarity with tools like Jira and Confluence.
• Knowledge of CI/CD for data workflows and version control using Git.

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