Job Description:
We are seeking a talented ETL/BI Engineer to design, develop, and maintain robust data pipelines, semantic models, and business intelligence solutions. The ideal candidate will have hands-on experience with AWS Glue, Amazon Redshift, and building modern semantic layers using tools like LookML (Looker) and Cube. You will be instrumental in shaping scalable data architecture, enabling self-service analytics, and delivering reliable insights across the organization.
Fluent English is required, as this role involves collaboration with international teams and stakeholders.
Key Responsibilities:
* Design, implement, and optimize ETL workflows using AWS Glue and other AWS services.
* Build and maintain data warehouses using Amazon Redshift, ensuring scalability, performance, and cost-efficiency.
* Develop and manage semantic layers using LookML (Looker) and Cube to standardize metrics and simplify data access for business users.
* Create scalable, reusable data models and data marts to support analytics and reporting needs.
* Collaborate closely with data analysts, engineers, and stakeholders to translate business requirements into technical solutions.
* Ensure data integrity, quality, and consistency across the full data lifecycle.
* Automate and monitor data integration workflows, and maintain comprehensive documentation.
Qualifications:
* 3+ years of experience with ETL/ELT processes and cloud-based data pipelines, especially using AWS Glue.
* Strong proficiency in Amazon Redshift, including data modeling and query performance optimization.
* Hands-on experience with LookML for Looker semantic modeling.
* Familiarity or experience with Cube (https:
//cube.Dev/) for building headless BI and semantic APIs is highly desirable.
* Proficiency in SQL and scripting languages (e.G., Python).
* Experience with BI tools such as Looker, QuickSight, Tableau, or Power BI.
* Solid understanding of data governance, lineage, and metadata management.
* Strong communication and collaboration skills.
* Fluent English required.