Data Engineer

Responsibilities:

• Design and develop scalable ETL/ELT pipelines to ingest and transform data from various sources.
• Build and maintain data models and transformations using DBT in Snowflake.
• Work closely with analysts and business users to deliver Power BI dashboards and datasets.
• Integrate and automate data extraction from external APIs using Python, loading clean data into Snowflake.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Optimize and monitor data workflows in ADF, AWS Glue, or similar tools.
• Work with relational databases and ensure data integrity, quality, and performance.
• Maintain documentation and follow best practices for data engineering workflows.
• Support data migration or integration efforts with SAP BW systems (a plus, not mandatory).

Required Skills:

• Strong experience with Snowflake (data modeling, performance tuning, warehousing concepts).
• Proficiency in DBT (Data Build Tool) for transformation pipelines.
• Hands-on experience with Power BI (data modeling, DAX, visualization best practices) or other tools like SAC/Tableau.
• Solid knowledge of Python, especially for API integrations and data processing.
• Experience with cloud-based data pipeline tools, such as Azure Data Factory (ADF) and/or AWS Glue.
• Good understanding of relational databases, SQL, and data modeling concepts.
• Strong problem-solving skills and ability to work independently or in a team.
• Excellent communication and documentation skills.

Nice to Have:

• Exposure to SAP BW data sources or integration with Snowflake.
• Experience with DevOps tools for data (CI/CD, version control in data workflows).
• Familiarity with orchestration tools like Airflow or Azure Data Factory triggers