Junior Data Engineer

Position Requirements:
Must be fluent in hashtag#SQL/SQL packages/Views/Triggers in the following environments (preferably SQL Server, Oracle, DB2). Must have completed at least one full cycle of building a data lake and/or a data warehouse, and orchestration of data movement from source to target (with proper mapping, formatting and transformation) through data pipelines such as Azure Data Factory.
5+ years of experience working with Python, PySpark and Jupyter/Databricks notebooks.
2+ years of experience in cloud technologies - Microsoft Azure would score higher, but AWS and GCP will be considered.
Ability to learn scheduling tools such as Cawa and Cleo Harmony.
1+ years of experience in CI/CD process such as Jenkins, GitHub or Azure DevOps
Experience working with one or more analytical systems (Databricks, Snowflake, Redshift, Big query, Azure Synapse, etc.) and ETL/ELT processes.
Knowledge and skills with Power BI will be important, not critical.
Problem solving skills to address complex data engineering challenges.
Ability to multi-task and change course with priorities.
Strong business communications skills for requirements gathering and development.
Must have a foundational knowledge of data science concepts, including causal inference and predictive modeling.
Should meet at least 75% of the skills listed in the sections of Position Responsibilities listed above.
Worked with or built Data Lakes, Data Warehouse in a hybrid environment (cloud / on premises).
Good understanding of data modelling , mapping and a through data quality /governance practices
Qualifications:
5+ years overall data warehouse and/or data lake methodologies, and data solution deliveries.
3+ years of experience as a data engineer and/or software engineer.
3+ years of experience building ETL/ELT processes in Azure.
2+ years of experience working with Azure Data Engineering workflow orchestration tools such as Azure Data Factory, Azure Databricks Pipelines
Bachelor's Degree or equivalent professional experience