• B.S. or M.S. studies in Computer Science/Information Technology / Statistics / Mathematics / Management Information Systems
• Advanced SQL database querying and scripting
• Strong knowledge of a scripting language (preferably Python) and proven knowledge of OOP and Design Patterns
• Experience with version control systems such as Git
• Represents a big plus experience with any of the following: Snowflake, dbt (data build tool) / SQLMesh /Dataform / similar, Dagster / Prefect / Airflow, Docker, Azure Container Apps / Azure App Functions, Azure Event Hubs, Power BI Semantic Models (Tabular)
• Proven previous experience in working as part of Data Engineering, Data Integration or Business Intelligence teams for Product companies creating data-oriented software solutions
• Good understanding of data warehousing methodologies (Kimball, Inmon, Data Vault 2.0)
• Good understanding of data modelling practices (relational, entity-relationship, object-oriented, flat, query-first)
• Good understanding of data engineering design patterns (raw loads, replication, batch ETL, streaming ETL, ELT, stream processing, data virtualization, change data capture)
• Understanding of declarative & imperative database deployment patterns and proven usage of tools like Terraform, Flyway, Schema Change, Liquibase or anything else similar
• Strong analytical skills in collecting, organizing, and analyzing significant amounts of data
• Strong knowledge of a typical SDLC
• Must be a self-starter, with the ability to work independently, with different groups and teams, utilizing solid communication skills.
• Ability to work in cross-functional teams
• Great communication and people skills with an experience of onsite/offshore model