Data Engineer (3 Days in OFFICE :: W2 ONLY)

The Opportunity: We are seeking a highly motivated and enthusiastic Data Engineer to join our data team. This is an excellent opportunity in building and maintaining data pipelines within a modern cloud-based data ecosystem. You will play a key role in ensuring our data is accurate, accessible, and ready for analysis, supporting various business functions.

Responsibilities:

• Assist in the design, development, and maintenance of ETL (Extract, Transform, Load) processes to ingest data from various sources into our data warehouse.
• Write and optimize Python scripts for data extraction, transformation, and loading, ensuring data quality and efficiency.
• Work with our Azure cloud platform to provision, configure, and manage data services such as Azure Data Lake Storage, Azure SQL Database, and potentially Azure Data Factory.
• Develop and maintain data schemas and tables within Snowflake, our cloud data warehouse.
• Collaborate with senior data engineers and data analysts to understand data requirements and assist in translating them into technical solutions.
• Monitor data pipelines for performance and data integrity issues, troubleshooting and resolving problems as they arise.
• Participate in data quality initiatives, identifying and addressing discrepancies in data.
• Document data flows, ETL processes, and data models to ensure clear understanding and maintainability.
• Learn and apply best practices in data engineering, data governance, and data security.
• Contribute to the continuous improvement of our data platform and tooling.

Required Skills and Experience:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
• 3-5 years of professional experience in a data-related role (e.g., intern, data analyst, entry-level developer) with a strong desire to specialize in data engineering.
• Strong foundational knowledge of Python and experience with its data manipulation libraries (e.g., Pandas).
• Understanding of ETL (Extract, Transform, Load) concepts and data warehousing principles.
• Familiarity with cloud platforms, specifically Microsoft Azure, including an understanding of services like Azure Data Lake Storage or Azure SQL Database.
• Basic understanding of relational databases and SQL.
• Eagerness to learn and work with Snowflake as a cloud data warehouse.
• Excellent problem-solving skills and a keen eye for detail.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.