Key Technical Skills:

Solid experience in cloud data environments, with a focus on AWS (Amazon Web Services) — services such as S3, Glue, EMR, Redshift, Lambda, and others.

Experience with Databricks, including development and optimization of notebooks, jobs, and integration with other tools in the data ecosystem.

Knowledge and application of observability in data pipelines – use of monitoring, logging, tracing, and alerting tools to ensure data quality and reliability.

Ability to create and maintain reusable templates and frameworks for data pipeline orchestration.

CI/CD for data practices, automation of deployments, and code versioning.

Experience with data engineering best practices, such as modeling, partitioning, governance, and information security.

Architecture and Performance Tuning in Power BI: optimization of models, DAX, workspace governance, and best practices for corporate environments.

Gateway cluster administration and access management for secure integration between environments and users.

Desirable Differentiators:

AWS or Databricks certifications.

Experience in high-volume data environments (Big Data).

Knowledge of Apache Airflow, dbt, Spark, or other transformation and orchestration tools.

DevOps/DataOps mindset.