Senior / Data Engineer (Data Architecture, Modeling & Modern DWH)

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 we're 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 welcomed—without 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:

We're hiring a Senior Data Engineer who's done more than execute pipelines inside someone else's design. If you've independently architected a data model — Star Schema, Data Vault, or a Medallion (bronze/silver/gold) Lakehouse — and can walk through the trade-offs you made, not just the tools you used, keep reading.

What you'll actually own:

• Design and own dimensional and Lakehouse data models from scratch — Star Schema, Snowflake Schema, Data Vault, or Medallion architecture, chosen for the problem, not defaulted to
• Build ETL/ELT pipelines you'd trust without watching them — CDC, incremental loads, watermarking, real error handling, the stuff that doesn't page you at 2am
• Go deep on Databricks (Delta Lake, Unity Catalog, cluster tuning, Z-Order) or Snowflake (multi-cluster warehouses, clustering keys, performance tuning) — architecture and platform ownership, not notebook execution
• Use PySpark and Spark SQL for real distributed processing at scale
• Write SQL that holds up under production load, not just queries that return the right answer once

What we need to see, not just hear about:

• 4–8 years of hands-on data engineering, with modeling you designed independently — able to explain why you chose the schema you chose
• Real ownership of Databricks or Snowflake at the architecture level, not just usage
• Strong Python and PySpark
• Azure (ADF, ADLS, Synapse) and/or AWS (S3, Glue, EMR, Redshift) — production experience, not a course completion
• Bachelor's in Computer Science, Data Engineering, or related field

Nice to have, not a gate:

• Power BI or Tableau — genuinely valued, but we won't screen out a strong architecture-first engineer who partners with BI rather than builds dashboards themselves
• Kafka or Kinesis, dbt, Microsoft Fabric
• DP-203, Databricks Data Engineer Associate, SnowPro Core, or PL-300

We work with enterprise clients where the data problems are genuinely hard and the ownership is real. If that's the kind of work you're looking for, we should talk.

Benefits:

At Calfus, we value our employees and offer a strong benefits package. This includes medical, group, and parental insurance, coupled with gratuity and provident fund options. Further, we support employee wellness and provide birthday leave as a valued benefit.

Calfus is an Equal Opportunity Employer.

We believe diversity drives innovation. We're committed to creating an inclusive workplace where everyone—regardless of background, identity, or experience—has the opportunity to thrive. We welcome all applicants!