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 :

As a Senior Data Architect, you will lead the design, implementation, and governance of enterprise-grade data architectures that serve as the foundation for organizational analytics and AI-driven decision-making.

You will architect cloud-native data platforms using modern medallion architectures, design semantic data models, and establish data governance frameworks that scale across complex enterprise ecosystems.

This is a highly technical, hands-on leadership role that demands deep expertise in data modeling, cloud platforms (Snowflake, Databricks, Azure), and the ability to mentor engineering teams while driving strategic data architecture initiatives.

What You'll Do :

- Architect enterprise data platforms using medallion (bronze-silver-gold) layering strategies for scalable, maintainable analytics ecosystems.

- Design and implement semantic data models that enable self-service analytics, reduce complexity, and improve business alignment.

- Lead dimensional, relational, and analytical schema design for complex multi-source data environments.

- Own foundational data architecture strategies that balance performance, scalability, cost, and usability.

- Design and implement cloud-native data architectures on Snowflake, Databricks, or Azure cloud ecosystems.

- Architect ETL/ELT pipelines and data ingestion frameworks for high-volume, multi-source enterprise data ecosystems.

- Establish reusable data frameworks, platform abstractions, and architectural best practices to drive long-term scalability.

- Lead performance tuning, cost optimization, and capacity planning across cloud data platforms.

- Design and govern metadata, data catalogs, and semantic layers to enable discoverability and trustworthiness.

- Implement comprehensive data quality frameworks, validations, and observability practices.

- Establish data governance policies, lineage tracking, and compliance standards across the platform.

- Write complex SQL, Python, and data transformation code alongside your team - not just provide direction.

- Lead greenfield data architecture initiatives from conceptualization through production deployment.

- Design and optimize database schemas, indexing strategies, and query execution plans for analytical workloads.

- Mentor and develop junior data engineers, fostering a culture of technical excellence.

- Partner with BI teams to enable semantic modeling and self-service analytics on Power BI or Tableau.

- Translate complex business requirements into scalable, maintainable data architecture solutions.

- Drive cross-functional initiatives and communicate technical architecture decisions to executive stakeholders.

- Support data visualization teams with optimized data structures and APIs for reporting and dashboarding.

Requirements :

- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.

- 8 - 12 years of hands-on experience designing and architecting enterprise data solutions.

- Expert-level proficiency with Snowflake or Databricks.

- Advanced SQL expertise with experience across modern data platforms.

- Strong hands-on experience with cloud services (AWS, Azure, GCP) and data tools.

- Proficiency in Python for scripting, automation, data manipulation, and framework development.

- Deep understanding of data serialization formats (Parquet, JSON, CSV, Delta Lake formats).

- Demonstrated ability to design scalable data platforms that handle complex enterprise analytics at petabyte scale.

- Leadership experience mentoring data engineering teams or leading technical workstreams.