Data Engineer

Company Description Interexy is a custom software development and IT consulting company founded in 2017 and headquartered in Miami, delivering solutions across healthcare, FinTech, blockchain, IoT, real estate, e-commerce, and social networks. The company has strong expertise in mobile and web app development, blockchain, UI/UX design, cloud computing, Artificial Intelligence, and Machine Learning. Interexy collaborates with global brands such as SAP, PwC, Pampers, General Electric, and high-growth businesses across multiple markets. With over 150 successful projects, Interexy focuses on tailored, scalable solutions that help clients stay competitive in a rapidly evolving digital landscape. Team members join a culture centered on innovation, quality, and end-to-end product ownership.
Role Description This is a full-time remote role for a Data Engineer at Interexy. The Data Engineer will design, build, and maintain scalable data pipelines and ETL processes to support analytics and product teams across various industries. Responsibilities include modeling and organizing data structures, implementing and optimizing data warehouses and data lakes, and ensuring data quality, reliability, and performance. The role involves collaborating closely with software engineers, data analysts, and stakeholders to understand data requirements, define technical solutions, and continuously improve the data architecture. The Data Engineer will also monitor production data workflows, troubleshoot issues, and contribute to best practices and documentation for data infrastructure.
Qualifications
Fluent English communication skills (written and spoken) for daily collaboration with international stakeholders.
3+ years of professional experience in Data Engineering.
Strong Data Engineering skills, including building and maintaining data pipelines and supporting modern data platforms.
Experience with Data Modeling and Data Warehousing for analytical and transactional workloads.
Hands-on experience with Extract Transform Load (ETL) processes and tools to integrate data from multiple sources.
Ability to work with Data Analytics teams, enabling reporting, dashboards, and insight generation.
Proficiency in SQL and at least one programming language commonly used in data engineering (e.g., Python, Java, or Scala).
Strong hands-on experience and solid knowledge of cloud data services (AWS, GCP, or Azure) and modern data stack components (e.g., Spark, Kafka, Airflow, dbt).
Understanding of data security, governance, and best practices for privacy and compliance.
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 in a remote, distributed team.
Experience in software development or consulting environments and interest in domains such as healthcare, FinTech, or blockchain is a plus.
German language proficiency (B2+) is a strong plus.
Valid EU work authorization, residency, or citizenship (EU Permit / PR / Citizenship) is strictly required.

Work arrangement
Yes