Senior Data Engineer (WFH)

About the Role:

We are looking for a Data Engineer who will play a critical role in designing, building, and maintaining our data infrastructure to support analytics, reporting, and business intelligence. They will work closely with engineers, data scientists, and business stakeholders to ensure the efficient processing, storage, and accessibility of high-quality data.

This role is ideal for an engineer with a strong background in cloud-based (AWS) data engineering, automation, and DevOps practices, looking to work in a fast-paced, data-driven environment.

• 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.

Desirable:

• 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.