Sr. AI & Data Engineer – Snowflake
$70k - $206k • Dallas, 5205 N OConnor Las Colinas, Corp
Posted 1d ago
About the job
We are seeking a best-in-class, hands-on Snowflake Data & Analytics Engineer with deep expertise in building modern, cloud-native data solutions. You will design, build, and operationalize enterprise-grade data and agentic AI solutions on the Snowflake AI Data Cloud. You will own the full lifecycle of Snowflake-native data products and agentic AI systems, from architecture and ingestion through to production deployment, governance, and continuous improvement. This role is ideal for someone curious, detail-oriented, and passionate about writing clean, efficient code, who thrives in fast-paced environments and is motivated by solving hard data problems that unlock business value. You will be part of a highly collaborative and growing network of technology and data experts, taking on today's biggest, most complex business challenges using the latest data and analytics technologies.
Responsibilities
- Architect and maintain a scalable, governed Snowflake AI Data Cloud environment, including compute optimization, warehouse sizing, and cost management.
- Design and implement ELT/ETL frameworks using Snowflake SQL, Snowpark Python, Dynamic Tables, Streams, Tasks, and Snowpipe for various ingestion patterns.
- Build reusable, AI-ready data products with clear ownership, semantic context, data quality SLAs, and lineage tracking.
- Implement enterprise security controls such as RBAC/ABAC, column- and row-level security, dynamic data masking, classification tags, and audit logging.
- Integrate Snowflake with upstream source systems, orchestration platforms (e.g., dbt, Apache Airflow), governance tools, and downstream analytics consumers.
- Design and build multi-step agentic AI workflows using Snowflake Cortex Agents, Cortex AI Functions, Cortex Search, and Cortex Analyst.
- Develop production-grade Retrieval-Augmented Generation (RAG) pipelines with vector search, semantic retrieval, and hybrid search capabilities over governed Snowflake datasets.
- Implement tool-use orchestration, prompt engineering, and evaluation frameworks (LLMOps) for reliable, auditable AI agent behavior.
- Apply agentic automation to operational use cases including anomaly detection, data quality remediation, query diagnosis, documentation generation, and incident summarization.
- Integrate AI agents with enterprise systems via MCP (Model Context Protocol) connectors, REST APIs, and event-driven messaging architectures.
- Define and enforce data modeling standards (Kimball dimensional, Data Vault 2.0) to support analytics, ML feature stores, and AI consumption layers.
- Build and maintain semantic data models that expose governed, business-ready datasets to Cortex Analyst and BI tools.
Requirements
- A minimum of three years of professional experience in data engineering, including building agentic AI or LLM-powered applications (RAG pipelines, tool-use agents, prompt engineering) in an enterprise context.
- A minimum of three years of professional experience with Snowflake-native features: Snowpark (Python), Dynamic Tables, Streams & Tasks, Snowpipe, Cortex AI suite, and performance tuning.
- A minimum of three years of experience with Python for data engineering and ML workloads, and advanced SQL.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience).
- Experience with data modeling methodologies and dbt for transformation layer management.
- Familiarity with at least one major cloud platform (AWS, Azure, or GCP) and associated services.
- Experience implementing data governance, security policies, and compliance frameworks on cloud data platforms.
- Strong problem-solving skills and attention to detail.