
Chief Data Architect
1 day ago
We are looking for an experienced Data Engineer to join our team and play a key role in designing, building, and maintaining our data infrastructure.
The ideal candidate will have strong experience in cloud-based data engineering, automation, and DevOps practices, and be able to work closely with engineers, data scientists, and business stakeholders to ensure the efficient processing, storage, and accessibility of high-quality data.
Responsibilities:
- Data Infrastructure & Pipelines: Design and develop 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.
Requirements:
- 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.
Desirable Skills:
- 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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