Data Engineer

Listed as a remote role based in Estonia. Cymoro is building AI-powered digital twins and simulation systems that help small and medium-sized businesses understand risks, identify opportunities, test possible actions, and make better decisions. We’re looking for a hands-on Data Engineer to help design and build the scalable data infrastructure behind our platform. What you’ll work on Build and maintain scalable data pipelines for structured and unstructured data. Design AI-powered data collection workflows that extract, classify, enrich, validate, and structure information from APIs, websites, documents, public datasets, user inputs, and third-party sources. Develop reliable workflows combining traditional data engineering with LLMs, AI agents, retrieval systems, and automated validation. Create and maintain data models for digital twins representing products, companies, organisations, customers, markets, people, and simulation environments. Clean, normalize, deduplicate, reconcile, and version data from multiple sources. Implement data-quality controls, schema validation, monitoring, lineage, logging, retries, and failure recovery. Prepare data for AI agents, semantic search, vector retrieval, analytics, forecasting, and simulation engines. Build integrations between databases, application services, AI workflows, and simulation systems. What we’re looking for Strong experience with Python and SQL. Experience building ETL/ELT pipelines and data-ingestion systems. Strong understanding of databases, data warehouses, data modelling, and schema design. Experience integrating APIs, webhooks, cloud storage, databases, and external data sources. Familiarity with AWS, Snowflake, MongoDB, Databricks, PostgreSQL, or similar technologies. Experience with orchestration tools such as Airflow, Dagster, Prefect, dbt, or equivalent. Understanding of automated testing, CI/CD, Git, monitoring, and logging. Awareness of data governance, privacy, access control, and secure data handling. AI coding skills We are looking for someone who can use modern AI coding tools to work faster and more efficiently while maintaining strong engineering standards. You should be comfortable using tools such as GitHub Copilot, Codex, Claude Code, Cursor, or similar platforms to support: Coding and refactoring Testing and debugging SQL and schema generation Documentation Infrastructure configuration Codebase analysis Automation of repetitive engineering tasks AI-generated code must still be reviewed, tested, secured, and validated before production use. Valuable additional experience Experience in any of the following would be a strong advantage: LLM APIs and AI-agent workflows Structured outputs and tool calling Retrieval-augmented generation Embeddings and vector databases Web-data extraction and document processing Entity resolution or knowledge graphs Machine-learning pipelines Forecasting or simulation systems Event-driven architectures Migration from low-code prototypes to production infrastructure Early-stage startup environments Who you are You are comfortable working in an early-stage environment, solving ambiguous problems, taking ownership, and helping shape the technical direction of the product. You care about data quality, scalability, traceability, maintainability, and delivery speed. You know when to use low-code tools, when to write custom systems, and how to use AI tools without compromising engineering quality. Show more Show less Seniority level Entry level Employment type Contract Job function Information Technology Industries Artificial Intelligence