MUST HAVES

• 5+ years of experience with Scala (preferred) OR Java for data engineering and ETL;
• 5+ years of experience with data pipeline tools such as Spark;
• 5+ years of experience working in the AWS ecosystem (preferred), or GCP;
• High proficiency in SQL programming with relational databases – experience writing complex SQL queries is a must;
• Experience in using the best practices of Cloud provider AI services;
• Ability to contribute in an agile, collaborative, and fast-paced environment;
• An excellent problem-solving ability, to like to think outside of the box to solve common problems;
• Upper-intermediate English level.

• Design, develop, maintain, and enhance highly scalable data engineering solutions leveraging AWS services;
• Design, build, document, and implement scalable pipelines with a clear focus on data quality and reliability;
• Ingest and transform structured, semi-structured, and unstructured data from multiple sources;
• Build an enterprise-level ETL/ELT solution;
• Innovate and build proprietary algorithms to tackle complex problems involving interesting data challenges;
• Execute and continually optimize new customer data ingestion and model implementation processes;
• Integrate business knowledge with technical functionalities;
• Often work collaboratively with application engineers, data scientists, product managers, and product delivery teams;
• Develop solutions at the intersection of data and ML;
• Monitor workflow performance, and reliability, and ensure SLA targets are met;
• Automate existing code and processes using scripting, CI/CD, infrastructure-as-code, and configuration management tools;
• Work with AI (AI is at the heart of everything we do, and if you desire to be closer to the AI scene, we have opportunities to work on problems like NLP, image analysis featurization, and OCR labeling).