Principal Data Engineer

BlueCloud is a Snowflake Elite Partner and the 2026 CoCo Catalyst Snowflake Partner of the Year. We help enterprise organizations move from fragmented legacy systems to unified, AI-ready Snowflake platforms delivering data migration, engineering, governance, BI & analytics, and AI/ML solutions 4050% faster than traditional approaches.

With 450+ Snowflake consultants, 200+ enterprise transformations under our belt, and a 100% Snowflake focus, we combine advisory-led thinking with AI-powered accelerators to turn months of work into weeks of results. Our clients span Financial Services, Healthcare & Life Sciences, Retail, Manufacturing, Energy, and more — and the outcomes speak for themselves: 97% faster reports, 40% fraud reduction, $1.5M in client savings, and 10 client growth.

We don't just strategize — we execute.

About the Role

BlueCloud is seeking an experienced Principal Data Engineer – Snowflake to lead the design, development, and delivery of enterprise-scale data solutions built on Snowflake.

This is a highly technical, hands-on principal-level role focused on Snowflake architecture, data engineering, data migration, data modeling, performance optimization, governance, and enterprise data platform development.

You will work across complex enterprise environments to design and implement scalable Snowflake solutions that support analytics, business intelligence, operational workloads, and increasingly AI/ML use cases.

The ideal candidate has deep, hands-on Snowflake experience combined with strong data engineering and architectural skills. You should be comfortable making technical architecture decisions, solving complex Snowflake problems, establishing engineering standards, and mentoring other engineers while remaining hands-on with implementation.

Key Responsibilities

- Lead the architecture, design, and implementation of enterprise-grade Snowflake data platforms.
- Design scalable Snowflake architectures supporting enterprise analytics, BI, operational workloads, and AI/ML use cases.
- Develop complex ETL/ELT pipelines and data integration solutions using Snowflake and modern data engineering technologies.
- Design and implement robust data models, including dimensional, normalized, denormalized, and analytical data models.
- Perform Snowflake data migrations from legacy databases, data warehouses, and other platforms.
- Design and implement Snowflake solutions using Streams, Tasks,



Stored Procedures, Dynamic Tables, Snowpipe, Snowpipe Streaming, and other Snowflake capabilities.
- Optimize Snowflake workloads for performance, scalability, reliability, and cost efficiency.
- Implement Snowflake security and governance, including RBAC, masking policies, row access policies, secure views, data classification, and access controls.
- Design solutions for data quality, data lineage, metadata management, and enterprise data governance.
- Develop and optimize complex SQL and Python-based data processing solutions.
- Work with Snowpark to develop scalable data engineering and data processing workloads where appropriate.
- Design integrations between Snowflake and APIs, applications, cloud services, streaming platforms, and other enterprise systems.
- Troubleshoot complex Snowflake performance, data quality, pipeline, and production issues.
- Establish reusable Snowflake engineering patterns, frameworks, coding standards, and best practices.
- Lead technical design sessions and make architecture decisions for complex data engineering initiatives.
- Review technical designs and code produced by other engineers and provide architectural and technical guidance.
- Mentor Senior Data Engineers and help raise engineering standards across the team.
- Work directly with Data Architects, Solution Architects, AI/ML Engineers, application teams, and client stakeholders.
- Translate business and architectural requirements into scalable, production-ready Snowflake solutions.
- Support technical discovery, estimation, solution design, and delivery planning for enterprise client engagements.
- Stay current with new Snowflake capabilities and identify opportunities to improve existing platforms and solutions.

Required Qualifications
- 8–12+ years of experience in data engineering, data architecture.
- Deep hands-on experience with Snowflake in enterprise production environments.
- Proven experience designing and implementing large-scale Snowflake data platforms and architectures.
- Strong expertise in Snowflake SQL and advanced SQL development.




- Robust Python development experience for data engineering and automation.
- Extensive experience designing and implementing ETL/ELT pipelines.
- Strong understanding of data warehousing and modern data architecture principles.
- Strong experience with data modeling, including dimensional modeling and enterprise data warehouse design.
- Hands-on experience with several Snowflake capabilities, including:

- Snowflake Streams

- Snowflake Tasks

- Stored Procedures

- Snowpipe / Snowpipe Streaming

- Dynamic Tables

- Time Travel
- Zero-Copy Cloning

- Secure Views

- Materialized Views

- Snowflake Resource Monitors
- Strong understanding of Snowflake performance optimization and cost optimization.
- Strong experience with Snowflake security, including:

- RBAC

- Role hierarchy

- Row Access Policies

- Masking Policies

- Secure Views

- Data classification

- Access controls
- Experience with Snowflake data migration and modernization projects.
- Experience integrating Snowflake with cloud platforms, APIs, applications, and other enterprise data systems.
- Strong understanding of data quality, governance, lineage, and metadata management.
- Experience with Git, CI/CD, automated testing, and contemporary software engineering practices.
- Experience troubleshooting complex production data and Snowflake issues.
- Demonstrated ability to provide technical leadership and architectural guidance to other engineers.
- Excellent communication skills and the ability to work directly with technical and business stakeholders.

- Snowflake certification

What We're Looking For We are looking for someone who is recognized as a Snowflake subject-matter expert and can operate at both the architectural and implementation levels.

The successful candidate should be able to:

- Design a Snowflake architecture from the ground up.
- Make complex architectural decisions around Snowflake.
- Build and optimize sophisticated Snowflake pipelines.
- Diagnose and resolve difficult Snowflake performance and data issues.
- Design secure and governed enterprise Snowflake environments.
- Lead Snowflake migrations and modernization initiatives.
- Establish engineering standards and reusable patterns.
- Mentor other data engineers.
- Communicate complex Snowflake concepts clearly to architects, engineers, clients, and business stakeholders

📌 Principal Data Engineer (Noida)
🏢 Sembridge Outsourcing Services
📍 Noida