Strong experience with Data Platform reference architectures (e.g. Lambda architecture, Data Mesh).
Deep knowledge of big data technologies (e.g., Hadoop, Spark, Kafka) and data warehousing solutions (e.g., Redshift, Snowflake).
Extensive experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud. Google Cloud certification is preferred.
Experience with migration from on-premise to cloud and vice versa.
Good knowledge of relevant security frameworks & standards.
Proficiency in programming languages such as Python, Java, or Scala.
Strong understanding of database management systems (e.g., SQL, NoSQL, NewSQL). Experience with SQL and database management systems (e.g., MySQL, PostgreSQL, SQL Server).
Knowledge of data integration tools and frameworks (e.g., Apache Nifi, Talend, Informatica).
Familiarity with data modeling, data warehousing and data governance practices.
Experience with Iaac (e.g. Ansible, Terraform), data pipeline orchestration (e.g. Airflow), log exploration tools (e.g. Streamlit, Dash), data extraction (e.g. PostGIS, Kafka, Airflow, FastAPI), pandas, scikit-learn, Docker.
Solid knowledge of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc.
