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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Snowflake Architect - DBT and Cortex AI - **Company:** Cognizant Technology Solutions Corporation - **Location:** Mettawa, IL, United States - **Salary:** $88,000.0 - $170,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Business Analytics Applications, Data Analysis, Computing Platforms, ARM Architecture, Automation of Tests, CA Workload Automation Ae, Microsoft Azure, Cloud Computing, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Masking, Data Security, Data Warehousing, Database Testing, DevOps, Github, Jinja (Template Engine), Python (Programming Language), Machine Learning, Role-Based Access Control, Cloud Services, Search Technologies, Shell Script, SQL Stored Procedures, PL-SQL, SQL Databases, Data Streaming, Google Cloud, Real Time Systems, Large Language Models, Snowflake, Apache Spark, Change Data Capture, Data Layers, Data Lakes, Pyspark, Data Analytics, Apache Kafka, Spark Streaming, Data Management, Machine Learning Operations, Terraform, Databricks, Control M - **Published:** July 11, 2026 - **Apply:** https://dejobs.org/x/x/43BB3BF505E249798103D5BB79E050F9/job/ ## About the Role * 15+ years of experience designing and delivering enterprise-scale cloud-native data platforms across AWS, Azure, and GCP. * Deep expertise in Snowflake, Snowpark, dbt Cloud, dbt Core, Databricks, Python, Spark (PySpark), and Informatica IICS. * Proven track record building scalable ELT frameworks, modern cloud data warehouses, Lakehouse architectures, and AI-ready analytics platforms. * Hands-on experience with Snowflake Cortex AI capabilities, semantic models, conversational analytics, and GenAI-powered analytics solutions built on Snowflake and Databricks. * Experience implementing enterprise data modeling using dbt - staging, intermediate, marts, semantic layers, dimensional models, SCD Type 1/2 processing, data quality testing, lineage, and automated documentation. * Strong background leading distributed engineering teams delivering secure, scalable, and cost-optimized cloud data platforms processing multi-terabyte enterprise workloads. * Working knowledge of streaming and real-time processing (Kafka, Spark Structured Streaming) and orchestration tools (Dagster, Control-M, AutoSys, UC4, Tidal). * Proficiency in Python, SQL, PL/SQL, and shell scripting, with DevOps/CI-CD experience using Terraform, GitHub, and Azure DevOps. * Strong grounding in data governance practices including RBAC, data masking, data quality, and regulatory compliance. CORE TECHNICAL EXPERTISE * Data Architecture: Lakehouse, Enterprise Data Warehouse, Medallion Architecture, Semantic Data Layer. * Snowflake Data Cloud: Snowpark, Snowpipe, Streams & Tasks, Time Travel, Zero-Copy Cloning, Secure Data Sharing, Dynamic Tables, Cortex Analyst, Cortex Search. * Snowpark & Advanced Analytics: Snowpark Python, Snowpark ML, DataFrames, UDFs, Stored Procedures, AI Functions, ELT frameworks. * AI / GenAI & Semantic Analytics: Semantic Models, Vector Search, LLM Integration, Conversational Analytics, RAG architectures, AI-ready data platforms. * Databricks: Delta Lake, PySpark, Delta Live Tables (DLT). * Data Engineering & Transformation: dbt Cloud, dbt Core, ELT design, incremental models, snapshots, seeds, sources, Jinja macros, data testing, documentation, CI/CD. * Streaming & Real-Time Processing: Kafka, Spark Structured Streaming. * Cloud Platforms: AWS, Azure, GCP. * Programming: Python, SQL, PL/SQL, Shell Scripting. * Orchestration: Dagster, Control-M, AutoSys, UC4, Tidal. * DevOps & CI/CD: Terraform, GitHub, Azure DevOps. * Data Governance: RBAC, Data Masking, Data Quality, Compliance. PREFERRED CERTIFICATIONS * SnowPro Core Certification * Databricks Certified Data Engineer Associate ## Description Cognizant is seeking a Data Engineering Lead / Data Architect with 15+ years of experience designing and delivering enterprise-scale, cloud-native data platforms across AWS, Azure, and GCP. This role owns the architecture, delivery, and governance of modern Lakehouse and cloud data warehouse platforms built on Snowflake and Databricks, and leads the build-out of AI-ready, GenAI-enabled analytics capabilities for enterprise clients. The ideal candidate combines deep hands-on dbt technical expertise with the ability to lead distributed engineering teams, mentor talent, and establish data engineering best practices across large-scale, multi-terabyte production environments., * Enterprise Data Architecture: Architect and deliver enterprise-scale Snowflake Data Cloud and Databricks Lakehouse platforms supporting modern data warehousing, ELT, AI, and self-service analytics. * Multi-Layer Platform Design: Design multi-layered data architectures (Raw, Curated, Business, Semantic) using Snowflake, dbt Cloud, and Snowpark Python. * Ingestion & Change Data Capture: Implement Snowpipe, Streams & Tasks, Dynamic Tables, external stages, CDC frameworks, and SCD Type 1/Type 2 processing for batch and near real-time ingestion. * ELT Framework Delivery: Build scalable ELT frameworks using dbt Cloud, Snowpark Python, and Snowflake SQL, incorporating reusable Jinja macros, incremental models, snapshots, automated testing, lineage, and documentation. * CI/CD & Environment Management: Configure dbt Cloud jobs, deployment environments, GitHub-based CI/CD, and reusable dbt-utils packages to standardize enterprise transformations and automate production releases. * Advanced Transformation Frameworks: Design and optimize Snowpark-based transformation frameworks using DataFrames, Python UDFs, stored procedures, and AI Functions. * Performance Engineering: Optimize Snowflake performance through query profiling, micro-partitioning, clustering keys, materialization strategy, warehouse right-sizing, resource monitors, and auto-suspend/resume configuration. * Governance & Security: Implement enterprise governance using RBAC, row- and column-level security, masking policies, Time Travel, Zero-Copy Cloning, secure data sharing, and external tables. * AI-Ready & GenAI Platforms: Design AI-ready data platforms leveraging Snowflake Cortex, Cortex Analyst, and Cortex Search, along with semantic models and vector search, to enable GenAI-powered and conversational analytics. * Cross-Platform AI/ML Integration: Integrate Snowflake with Databricks AI/ML ecosystems to enable advanced analytics, machine learning, semantic retrieval, and AI-powered business insights. * Team Leadership: Lead enterprise modernization initiatives end-to-end - from architecture through production deployment - while mentoring engineering teams and establishing cloud data engineering best practices. ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Got AI ideas but no money? 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