About the Role:

Sietrix Technologies is hiring a Principal Data Architect - Modern Data Platforms for one of our client engagements.

We are looking for a senior hands-on Data Architect who has real production experience in designing, building, and optimizing modern cloud data platforms. This is not a strategy-only or documentation-heavy architecture role. The right candidate should be able to own architecture decisions end-to-end while also being technically hands-on when required.

The ideal candidate will have strong experience with Snowflake, dbt, Python, SQL, data modelling, cloud-native data platforms, pipeline architecture, performance optimization, governance, and AI-ready data foundations.

We are looking for someone who has actually built scalable data platforms, solved Snowflake performance and cost challenges, handled complex enterprise data, and worked closely with engineering teams to deliver production-grade solutions.

Key Responsibilities:

- Own end-to-end architecture for modern cloud data platforms.

- Design scalable, secure, and reliable data ecosystems.

- Build and guide production-grade data ingestion, transformation, and data modeling frameworks.

- Lead Snowflake architecture, including performance tuning, warehouse strategy, workload scaling, storage optimization, and cost management.

- Design and implement batch, API-driven, and event-driven data ingestion frameworks.

- Work with dbt to build reusable, testable, and maintainable transformation models.

- Use Python and SQL for data engineering, automation, integration, and performance optimization.

- Design reliable orchestration, monitoring, observability, and pipeline failure-handling strategies.

- Establish enterprise-grade governance, access control, security, and data quality frameworks.

- Support AI/ML, advanced analytics, and LLM-related data initiatives through clean, governed, and AI-ready data architecture.

- Define modern engineering standards, reusable frameworks, and platform best practices.

- Work directly with engineering, business, and leadership teams to convert requirements into scalable technical solutions.

- Mentor data engineers and guide teams on architecture, design, and implementation best practices.

Required Skills:

- 8-12+ years of experience in Data Engineering, Data Architecture, or Modern Data Platform Engineering.

- Strong hands-on experience with Snowflake, dbt, Python, and SQL.

- Proven experience designing and building cloud-native data platforms from the ground up.

- Strong understanding of modern data architecture, data modeling, transformation strategies, orchestration, and pipeline scalability.

- Deep experience in Snowflake performance tuning, query optimization, warehouse sizing, compute/storage strategy, and cost optimization.

- Experience building scalable batch and real-time data pipelines.

- Experience with API-driven and event-driven data ingestion patterns.

- Strong knowledge of data governance, data quality, data lineage, security, access controls, and platform reliability.

- Experience handling large-scale enterprise data environments.

- Ability to move comfortably between architecture discussions and hands-on technical execution.

- Strong communication, problem-solving, and stakeholder management skills.

Good to Have:

- Experience supporting AI/ML or LLM-related data ecosystems.

- Experience with real-time streaming architectures.

- Experience in financial services, fintech, banking, insurance, or other regulated industries.

- Exposure to platform engineering or reusable data framework design.

- Experience with observability and data reliability tools.

- Experience with orchestration tools such as Airflow, Dagster, Prefect, or similar.

- Experience with cloud platforms such as AWS, Azure, or GCP.

- Experience with Kafka, Snowpipe, Fivetran, Matillion, Informatica, or similar data integration tools.

This Role Is Best Suited For Someone Who:

- Has built real production-grade modern data platforms.

- Can design architecture and also contribute hands-on when needed.

- Has strong Snowflake optimization and cost management experience.

- Understands both data engineering execution and enterprise architecture.

- Can guide engineering teams and make practical architecture decisions.

- Has worked on complex, messy, large-scale enterprise data environments.

- Can build scalable, governed, and AI-ready data foundations.

This Role Is Not Suitable For:

- Candidates with only reporting or dashboard development experience.

- Candidates who are only BI developers or BI architects.

- Candidates with only governance or documentation-focused architecture experience.

- Candidates with only support or maintenance experience.

- Candidates who have worked only on POCs and not real production platforms.

- Candidates who are not hands-on with Snowflake, dbt, Python, and SQL.

Why Join This Opportunity:

- Work on modern cloud data platform initiatives.

- Strong technical ownership and architecture influence.

- Opportunity to work with lean, high-impact engineering teams.

- Build scalable platforms instead of only creating documentation.

- Contribute to AI-ready data architecture and modern engineering standards.

- Work in a fast-moving environment with minimal bureaucracy and high technical depth.