Senior/Lead Data Engineer - ETL/Data Warehousing

About Calfus :

At Calfus, we are known for delivering cutting-edge AI agents and products that transform businesses in ways previously unimaginable. We empower companies to harness the full potential of AI, unlocking opportunities they never imagined possible before the AI era. Our software engineering teams are highly valued by customers, whether start-ups or established enterprises, because we consistently deliver solutions that drive revenue growth. Our ERP solution teams have successfully implemented cloud solutions and developed tools that seamlessly integrate with ERP systems, reducing manual work so teams can focus on high-impact tasks.

None of this would be possible without talent like you! Our global teams thrive on collaboration, and were actively looking for skilled professionals to strengthen our in-house expertise and help us deliver exceptional AI, software engineering, and solutions using enterprise applications.

As one of the fastest-growing companies in our industry, we take pride in fostering a culture of innovation where new ideas are always welcomedwithout hesitation. We are driven and expect the same dedication from our team members. Our speed, agility, and dedication set us apart, and we perform best when surrounded by high-energy, driven individuals.

To continue our rapid growth and deliver an even greater impact, we invite you to apply for our open positions and become part of our journey!

About the role :

As a Data Engineer BI Analytics & DWH, you will contribute to building scalable data infrastructure and efficient data pipelines that power our business intelligence and analytics capabilities. With 6-9 years of experience, youll apply your solid foundation in ETL/ELT development, data modeling, and database design to support data warehousing and data lake initiatives. You will also assist in enabling data visualization through tools like Tableau or Power BI.

What Youll Do : ETL/ELT Development :

• Design, build, and maintain efficient ETL and ELT processes using tools such as Azure data factory, Databricks, or similar orchestration frameworks.

• Ensure reliable data ingestion from various sources into centralized storage systems (DWH/data lakes).

Data Modeling & Warehousing :

• Design relational and dimensional data schemas tailored to business use cases in data lakes or traditional data warehouses (e.g., Snowflake, Redshift, Postgres).

• Develop and maintain data models optimized for analytics and reporting.

Database Engineering :

• Write efficient SQL queries and stored procedures to transform, clean, and aggregate data.

• Manage data transformations and complex joins to support analytical workloads.