The Role
Architects and builds enterprise Snowflake data platforms end to end, including ingestion, ELT, data modeling, semantic layers, BI enablement, governance, security, optimization, and observability. Leads modernization and migration efforts, integrates multi-source data, improves performance and cost efficiency, applies AI-enabled engineering workflows, and mentors teams while partnering with stakeholders on technical and business requirements.
Summary Generated by Built In
Role Overview
We are seeking a Lead / Principal Snowflake Engineer to architect and build scalable, enterprise-grade data platforms on Snowflake. This role will own the end-to-end data lifecycle, including ingestion, transformation, semantic layer implementation, and delivery of Front-end application.
You will act as a technical leader and architect, driving platform modernization, enforcing engineering standards, and ensuring performance, scalability, and cost efficiency.
Key Responsibilities1. Data Platform Architecture & Modernization- Design and build scalable Snowflake data platforms using best practices
- Assess legacy systems and define modernization and migration strategies
- Establish architectural standards, governance frameworks, and reusable patterns
- Develop end-to-end ELT pipelines from APIs, databases, SaaS platforms, and event streams
- Build reliable connectors with robust error handling, retry logic, and data consistency
- Transform raw data into clean, normalized, consumption-ready datasets
- Design dimensional data models (fact/dimension, star/snowflake schemas)
- Implement business-friendly semantic layers aligned with enterprise reporting needs
- Build aggregations, pre-computed metrics, and optimized data structures for analytics
- Develop advanced SQL transformations and implement performance tuning strategies
- Manage warehouse sizing, workload optimization, and cost governance
- Implement RBAC, data security, versioning, and data sharing mechanisms
- Align Snowflake data models with Power BI (DirectQuery and Import models)
- Optimize datasets for performance, scalability, and reporting efficiency
- Implement data validation, monitoring, and alerting frameworks
- Ensure high reliability and trust in downstream data consumption
- Leverage Snowflake Cortex, Agentic AI patterns, and AI tools to automate workflows and improve engineering productivity
- Provide technical leadership and mentor engineering teams
- Collaborate with stakeholders to define business and technical requirements
- Drive adoption of best practices in Snowflake and modern data engineering
- 10+ years of experience in data engineering, data architecture, or related roles
- Strong expertise in Snowflake (data modeling, performance tuning, governance, security)
- Proven experience building end-to-end data platforms from scratch
- Deep knowledge of semantic layer design and BI alignment
- Advanced SQL expertise (window functions, PIVOT, GROUPING SETS, etc.)
- Experience with multi-source data integration (RDBMS, APIs, SaaS, streaming)
- Strong cloud expertise (Azure/AWS) with Snowflake integration
- Proficiency in Python for data engineering and automation
- Familiarity with Agentic AI concepts and AI-driven tools to improve development efficiency and automation
- Experience with dbt (models, testing, lineage, documentation)
- Exposure to data observability tools (SODA.)
- Experience with SnapLogic, AWS S3, or equivalent services
- Experience with Snowflake Cortex / AI-based workflows
- Domain experience in Operation Data ( Cloud FinOps, AI Tool Ops, Managed Services Data, Agile Delivery Data will be Advantage.
- Ability to design, architect, and deliver Snowflake platforms end-to-end
- Strong focus on performance, scalability, and cost optimization
- Expertise in data modeling and semantic layer implementation
- Demonstrated technical leadership and stakeholder management
Skills Required
- 10+ years of experience in data engineering, data architecture, or related roles
- Strong Snowflake expertise, including data modeling, performance tuning, governance, and security
- Proven experience building end-to-end data platforms from scratch
- Deep knowledge of semantic layer design and BI alignment
- Advanced SQL expertise, including window functions, PIVOT, and GROUPING SETS
- Experience with multi-source data integration across RDBMS, APIs, SaaS, and streaming systems
- Strong Azure or AWS cloud expertise with Snowflake integration
- Proficiency in Python for data engineering and automation
- Familiarity with Agentic AI concepts and AI-driven tools for development efficiency and automation
- Experience with dbt models, testing, lineage, and documentation
- Exposure to data observability tools such as SODA
- Experience with SnapLogic, AWS S3, or equivalent services
- Experience with Snowflake Cortex or AI-based workflows
- Domain experience in operational data, including Cloud FinOps, AI Tool Ops, Managed Services Data, or Agile Delivery Data
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The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
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