## About the Role

BlueCloud is seeking an experienced Data Architect to lead the assessment, design, and modernization of enterprise data platforms, with a strong focus on Snowflake. The role combines architecture leadership, hands-on platform expertise, and direct client engagement.

You will define target-state architectures, evaluate existing data estates, and create modernization roadmaps that improve security, governance, performance, and cost efficiency. The work supports both current analytics needs and future AI and context-layer use cases.

This position works closely with engineering teams, analysts, QA specialists, DevOps teams, business stakeholders, and executive sponsors. The goal is to translate complex business requirements into practical architecture decisions and guide delivery from assessment through implementation.

## Key Responsibilities

– Lead architecture assessments and modernization efforts for enterprise Snowflake data platforms.
– Define current-state and target-state architectures across ingestion, transformation, storage, orchestration, governance, security, and consumption.
– Review Python-, SQL-, and stored-procedure-based pipelines and classify workloads by criticality, frequency, volume, runtime, reliability, and cost.
– Analyze Snowflake usage telemetry to establish cost and performance baselines.
– Identify architectural and engineering anti-patterns and recommend modernization approaches.
– Design scalable data models, governed data domains, semantic layers, and context models for analytics and AI use cases.
– Architect Snowflake Cortex solutions using Cortex Analyst, Cortex Search, and Cortex LLM functions.
– Establish standards for security, access control, governance, lineage, observability, performance, resilience, and business continuity.
– Design lakehouse and real-time data-processing architectures across AWS, Azure, or GCP.
– Evaluate Snowflake Iceberg Tables and other open data architecture patterns.
– Build prioritized optimization backlogs and delivery roadmaps based on business impact, risk, cost, performance, and effort.
– Provide technical leadership across multiple projects and guide engineers, analysts, QA specialists, and DevOps teams.
– Support planning, estimation, scope definition, dependency management, risk mitigation, and technical governance.
– Lead discovery workshops and stakeholder interviews.
– Present architecture decisions, findings, impact projections, and roadmap recommendations to technical and executive audiences.
– Maintain architecture diagrams, decision records, technical standards, and platform documentation.

## Required Skills

– 10+ years of experience in data architecture, data engineering, or a comparable senior technical role.
– 2–4 years of deep Snowflake architecture and implementation experience.
– Experience designing and modernizing enterprise-scale Snowflake data platforms.
– Strong knowledge of Snowflake environment design, security, governance, data modeling, workload management, and performance/cost optimization.
– Hands-on experience with Snowflake Snowpark, Dynamic Tables, Streams and Tasks, stored procedures, and system usage views.
– Expert-level SQL and strong Python skills.
– Experience with dbt and pipeline/orchestration technologies such as Fivetran, Kafka, Airflow, or similar tools.
– Experience designing batch, streaming, lakehouse, and cloud-native data architectures.
– Strong understanding of data governance, access control, lineage, data quality, and metadata management.
– Experience with at least one major cloud platform: AWS, Azure, or GCP.
– Proven ability to lead discovery, assessment, architecture, and modernization engagements.
– Experience leading multidisciplinary Agile delivery teams.
– Strong client-facing, presentation, and stakeholder-management skills.
– Ability to communicate complex technical concepts clearly to engineering teams, business leaders, and executive sponsors.

## Preferred Skills

– Hands-on experience with Snowflake Cortex, including Cortex Analyst, Cortex Search, or Cortex LLM functions.
– Experience building governed semantic or context layers for AI and LLM-based applications.
– Experience with Snowflake Iceberg Tables and open lakehouse architectures.
– Familiarity with Terraform, CI/CD, and infrastructure-as-code practices.
– Experience with FinOps, cloud cost governance, and Snowflake consumption optimization.
– Experience designing business continuity and disaster recovery solutions.
– SnowPro Advanced: Architect or SnowPro Core certification.
– Consulting or enterprise client-delivery experience.
– Experience acting as a technical delivery lead or Scrum Master when required.
– Familiarity with Jira, Confluence, and architecture tools such as Lucidchart.

## Cloud Platforms & Technologies

### Cloud Providers
– AWS
– Azure
– GCP

### Data Platforms
– Snowflake
– Snowflake Cortex
– Snowflake Iceberg Tables

### Programming Languages
– SQL
– Python

### Data Engineering / Transformation
– Snowpark
– Dynamic Tables
– Streams and Tasks
– Stored procedures
– dbt
– Fivetran
– Kafka
– Airflow

### Infrastructure as Code / Delivery
– Terraform
– CI/CD
– Infrastructure-as-code

### Collaboration / Documentation
– Jira
– Confluence
– Lucidchart

### Other
– System usage views
– AI / LLM-based applications
– Semantic layers
– Context layers
– Batch processing
– Streaming processing
– Lakehouse architectures
– Real-time data processing

## FinOps Responsibilities

– Analyze Snowflake usage telemetry to create cost and performance baselines.
– Identify workload and architecture inefficiencies that increase cloud spend.
– Recommend optimization strategies that improve cost efficiency and performance.
– Build roadmaps based on cost, business impact, and implementation effort.
– Support cloud cost governance and Snowflake consumption optimization.
– Contribute to secure, governed, cost-efficient platform design.

## Why You Might Be Interested

This role offers the chance to lead enterprise Snowflake modernization work from assessment through delivery. It combines architecture strategy, hands-on technical depth, and direct client advisory responsibilities. You will work across analytics, governance, AI-ready design, and cloud cost optimization. The position also provides exposure to a broad range of enterprise technologies and stakeholder groups.