Company Description Amorosia Ventures is a growing, innovation-focused organization that leverages data and technology to drive informed decision-making and long-term value. The company partners with a range of stakeholders to build scalable, data-driven solutions that support business growth and operational efficiency. Team members collaborate across functions to design modern data architectures and services. Amorosia Ventures values curiosity, accountability, and continuous improvement, and supports flexible, remote-friendly work practices.
Role Description As a Data Engineer at Amorosia Ventures, you will design, build, and maintain reliable data pipelines and infrastructure that support core analytics and product initiatives. In this full-time, remote role, you will develop and optimize Extract Transform Load (ETL) processes, integrate data from multiple sources, and ensure data quality, consistency, and security across environments. You will collaborate closely with data analysts, data scientists, and software engineers to model data for reporting and product use cases, and to support scalable data warehousing solutions. Day to day, you will write efficient, well-documented code, monitor pipeline performance, troubleshoot issues, and contribute to continuous improvements in data architecture and tooling. You will also help define best practices, participate in code reviews, and contribute to technical documentation for data systems.
Qualifications
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.

Data Engineer

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