Key skills
Data EngineeringData PipelinesLarge DatasetsData WorkflowsData ModelingData WarehousingETL ToolsSQLPythonScalaJavaCloud Data PlatformsData QualityData GovernanceData SecurityETLAnalyticsAWSAzureGCPCollaboration
About this role
Amorosia Ventures is a growing, innovation-focused organization that leverages data and technology to drive informed decision-making and long-term value. As a Data Engineer, you will design, build, and maintain reliable data pipelines and infrastructure to support analytics and product initiatives, collaborating with various teams to ensure data quality and scalability.
Responsibilities:
- Design, build, and maintain reliable data pipelines and infrastructure that support core analytics and product initiatives
- Develop and optimize Extract Transform Load (ETL) processes
- Integrate data from multiple sources and ensure data quality, consistency, and security across environments
- Collaborate closely with data analysts, data scientists, and software engineers to model data for reporting and product use cases
- Support scalable data warehousing solutions
- Write efficient, well-documented code, monitor pipeline performance, troubleshoot issues, and contribute to continuous improvements in data architecture and tooling
- Help define best practices, participate in code reviews, and contribute to technical documentation for data systems
Requirements:
- Strong Data Engineering skills, including building and maintaining data pipelines, working with large datasets, and implementing robust data workflows
- Proficiency in Data Modeling and Data Warehousing concepts, including designing schemas for analytics and scalable storage solutions
- Hands-on experience with Extract Transform Load (ETL) tools and frameworks to integrate, transform, and load data from diverse systems
- Familiarity with Data Analytics concepts and collaboration with analytics teams to support reporting, dashboards, and data-informed decisions
- Proficiency in SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java)
- Experience with cloud data platforms (such as AWS, Azure, or GCP) and modern data stack tools is highly beneficial
- Knowledge of data quality, data governance, and security best practices
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience
- Strong problem-solving skills, attention to detail, and the ability to work independently and effectively in a remote, collaborative environment