Oversee the development and optimization of SQL Server databases and queries to meet complex reporting and analytical needs.
Write and maintain Python scripts for sophisticated data transformation, analysis, and automation tasks.
Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand and translate data requirements into technical solutions.
Troubleshoot and resolve complex data-related issues, ensuring high data quality and reliability.
Monitor, optimize, and scale data workflows to improve performance and cost-efficiency.
Develop and enforce best practices for data engineering processes, documentation, and governance.
Requirements
2-4 years experience working with enterprise level relational and/or non-relational database and ETL/ELT technologies.
Extensive experience with Azure Data Lake Storage, Azure Data Factory, Databricks, SQL Server, and Python.
Demonstrated experience in the implementation and creation of both on-premise SQL Server Databases as well as Azure SQL Databases.
Deep understanding of data modeling, ETL processes, data warehousing concepts, and data architecture.
Advanced proficiency in SQL for complex querying and database management.
Strong experience with Python for advanced data manipulation and automation tasks.
In-depth knowledge of cloud computing concepts and services, particularly within Azure.
Excellent problem-solving abilities and attention to detail.
Exceptional communication skills and experience working collaboratively in a team-oriented environment.
Experience with data governance and data quality frameworks.
Familiarity with Azure services (e.g., Azure Synapse Analytics, Azure SQL Database, Cosmos DB) and big data technologies.
Experience with semi-structured/NoSQL databases is a plus.
Azure data certifications (e.g., Azure Data Engineer Associate) are a plus but not required.