Senior 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.