Filterbuy is seeking a Senior Data Engineer to lead the development of their modern analytics infrastructure, designing, building, and optimizing ETL pipelines, data models, and data warehouses to power reporting, analytics, and operational insights across finance, manufacturing, shipping, and marketing.
Requirements
- Proven experience working within the Amazon data ecosystem, including Amazon RDS, Amazon QuickSight, and related AWS services (e.g., S3, Glue, Redshift, Lambda).
- Proficiency in Python for ETL development, automation, and data manipulation.
- Strong command of SQL and experience designing and optimizing large-scale data models.
- Hands-on experience with Matillion or similar ETL/ELT orchestration tools.
- Familiarity with modern data stack tools such as dbt, Fivetran, Snowflake, and BigQuery.
- Knowledge of CI/CD, Git-based workflows, and infrastructure-as-code practices.
- Experience with AWS services like RDS, S3, Glue, and Lambda.
Responsibilities
- Design, build, and maintain ETL/ELT pipelines using Matillion and Python to extract, transform, and load data from diverse systems into Amazon RDS or other warehouse environments.
- Develop and optimize data models to support analytics, dashboards, and self-service reporting in Amazon QuickSight.
- Maintain and improve the AWS data infrastructure, ensuring reliability, performance, and scalability across services like RDS, S3, Glue, and Lambda.
- Implement data quality and validation frameworks, ensuring consistency and integrity throughout all pipelines.
- Partner with analysts and other data consumers to support end-to-end analytics workflows and improve data discoverability.
- Contribute to architectural decisions and mentor other data team members on best practices, coding standards, and data engineering patterns.
- Collaborate with business and technical stakeholders to define data needs, build scalable data solutions, and ensure data availability across the organization.
Other
- Bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related field.
- 5+ years of professional experience in data engineering or a similar technical role.
- Excellent analytical, problem-solving, and communication skills, with the ability to translate complex requirements into scalable data solutions.
- Ability to work in a remote environment.
- Equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics or any other legally protected category.
