> Markdown version of [/jobs/ext/1890466-snowflake-data-engineer](https://www.wearedevelopers.com/jobs/ext/1890466-snowflake-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Snowflake Data Engineer - **Company:** AIT Global, Inc. - **Location:** Alpharetta, GA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Adobe InDesign, Agile Methodology, Airflow, Amazon S3, Automation of Tests, CA Workload Automation Ae, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Data Governance, Data Security, Data Vault Modeling, Github, Apache Hadoop, Identity and Access Management, Oracle (Applications), Query Optimization, Role-Based Access Control, SQL Databases, Data Streaming, Teradata SQL, Data Processing, Data Ingestion, Snowflake, Sybase, Git, Dynamic Data, Terraform, Software Version Control, Jenkins, Control M - **Published:** July 31, 2026 - **Apply:** https://www.dice.com/job-detail/e4b00a30-8953-4c80-a063-9f7c30a6381b ## About the Role * 7+ years in data engineering; 4+ years hands-on Snowflake in a production environment. * Expert SQL - window functions, CTEs, complex joins, query optimization, execution plan analysis. * dbt (Core or Cloud) - models, macros, snapshots, tests, exposures. * Orchestration: Airflow, Control-M, or Autosys. * AWS: S3, IAM, Glue, Lambda, Secrets Manager. * CI/CD and IaC: Git, Jenkins/GitHub Actions, Terraform or Schema change for Snowflake object deployment. * Dimensional and Data Vault modeling; slowly changing dimensions; late-arriving data handling. * Demonstrated Snowflake cost-governance ownership (not just development). Preferred / Differentiators: * SnowPro Core / Advanced Data Engineer certification. * Prior tier-1 investment bank or large financial-services experience. ## Description Build and scale cloud data products on Snowflake supporting institutional trading, risk, and regulatory reporting. This is a hands-on build role - you will own pipelines end-to-end from ingestion through curated, governed consumption layers used by front-office, risk, and control functions., * Design, develop, and optimize Snowflake data models (staging integration semantic/consumption layers) for institutional trade, position, reference, and market data. * Build ingestion pipelines using Snowpipe / Snowpipe Streaming, Streams & Tasks, Dynamic Tables, and external stages against S3. * Develop transformation logic in SQL and dbt with version control, CI/CD, and automated testing. * Tune performance and cost: warehouse right-sizing, clustering keys, micro-partition pruning, query profiling, result caching, resource monitors, and credit-consumption reporting. * Implement data security and entitlements: RBAC hierarchy, dynamic data masking, row access policies, secure views, and secure data sharing across LOBs. * Migrate legacy Oracle / Teradata / Sybase / Hadoop workloads to Snowflake, including reconciliation and parallel-run validation. * Partner with data governance on lineage, cataloging, data quality rules, and audit/regulatory evidence. * Support production: incident triage, root-cause analysis, SLA adherence, and on-call rotation for critical batch cycles. * Work in Agile squads with BAs, QA, and platform engineering; participate in design reviews and code reviews. ## Related Videos - [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) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [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) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 162: AI careers, MCP, AWS best practices & floppy sweaters](https://www.wearedevelopers.com/magazine/571-dev-digest-162-ai-careers-mcp-aws-best-practices-floppy-sweaters) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)