Senior AI & Data Engineer - Snowflake

Salary: $54,400 - 205,800 per year Requirements:

• At least three years of professional data engineering experience, including enterprise experience building agentic AI or LLM-powered applications such as RAG pipelines and tool-use agents, and applying prompt engineering.
• At least three years of experience with Snowflake-native capabilities, including Snowpark (Python), Dynamic Tables, Streams and Tasks, Snowpipe, the Cortex AI suite, and performance tuning.
• At least three years of experience using Python for data engineering or machine learning workloads, and advanced SQL skills.
• A bachelors degree or equivalent experience (at least 12 years of work experience); an associate degree requires at least six years of work experience.
• Strong problem-solving skills, attention to detail, and the ability to work effectively in agile, cross-functional teams.
• Preferred: Experience with data modeling methods and dbt for managing transformation layers.
• Preferred: Familiarity with AWS, Azure, or GCP and related object storage, IAM, networking, and managed compute services.
• Preferred: Experience implementing data governance, security policies, and compliance frameworks on cloud data platforms.
• Preferred: A bachelors degree in computer science, software engineering, data science, or a related quantitative field; equivalent experience is also considered.
• Preferred: Snowflake SnowPro Advanced certification in Data Engineer or Architect, or Cortex AI practitioner credentials.
• Preferred: Experience with vector databases, such as Snowflake Vector Search, Pinecone, or Weaviate, and embedding models such as Snowflake Arctic Embed.
• Preferred: Hands-on experience with MLOps tools, including model registries, evaluation pipelines, experiment tracking, and production monitoring.
• Preferred: Familiarity with MCP (Model Context Protocol) and enterprise agentic control-plane architectures.
• Preferred: Exposure to streaming technologies such as Apache Kafka or Kinesis integrated with Snowflake ingestion pipelines.

• Own the lifecycle of Snowflake-native data products and agentic AI systems, from architecture and ingestion through production deployment, governance, and ongoing improvement.
• Architect and maintain a scalable, governed Snowflake AI Data Cloud environment, optimizing compute, warehouse sizing, and costs.
• Design and implement ELT/ETL frameworks with Snowflake SQL, Snowpark Python, Dynamic Tables, Streams, Tasks, and Snowpipe for batch, streaming, CDC, and event-driven ingestion.
• Create reusable, AI-ready data products with defined ownership, semantic context, data quality SLAs, and lineage tracking.
• Establish enterprise security controls, including RBAC/ABAC, row- and column-level security, dynamic data masking, classification tags, and audit logging.
• Connect Snowflake with source systems, orchestration platforms such as dbt and 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 RAG pipelines with vector search, semantic retrieval, and hybrid search over governed Snowflake data.
• Implement tool-use orchestration, prompt engineering, and LLMOps evaluation frameworks to support reliable, auditable AI agent behavior.
• Apply agentic automation to operational needs such as anomaly detection, data quality remediation, query diagnosis, documentation generation, and incident summarization.
• Integrate AI agents with enterprise systems using MCP connectors, REST APIs, and event-driven messaging architectures.
• Define and uphold data modeling standards, including Kimball dimensional modeling and Data Vault 2.0, for analytics, ML feature stores, and AI consumption layers.
• Build and maintain semantic data models that make governed, business-ready datasets available to Cortex Analyst and BI tools.

• Agentic AI
• AI
• AI Agents
• Airflow
• AWS
• Architect
• Azure
• Cloud
• Data Vault
• ETL
• Embedding Models
• GCP
• IAM
• Support
• Kafka
• LLM
• Machine Learning
• MCP
• MLOps
• Network
• Python
• RAG
• REST
• RBAC
• SQL
• Security
• Snowflake
• dbt

More:

We are hiring a Snowflake Data & Analytics Engineer to join Accentures Advanced Technology Centers (ATCs), a global network of more than 255,000 people across 24 countries. Our ATCs help clients address complex business challenges through technology, innovation, industry insight, and collaborative expertise. In this role, you will work with a growing, inclusive team of data and technology professionals across varied data engineering initiatives, with opportunities spanning data modeling, integration, analytics, pipelines, agentic AI, RAG, cloud and infrastructure integration, data quality, observability, and governance. This is a hybrid position requiring three days per week in the office, with hiring locations in Dallas or Houston, Texas; Columbus, Ohio; Atlanta, Georgia; or Tampa, Florida. Compensation varies by role, location, skills, and experience; the posting provides annual salary ranges for several U.S. states. We offer medical, dental, vision, life, and long-term disability coverage, a 401(k), bonus opportunities, paid holidays, and paid time off. Accenture is a global professional services company serving clients in more than 120 countries, combining technology, cloud, data, and AI expertise with industry experience and global delivery capabilities. We are committed to inclusion and diversity and to fostering a workplace where everyone can belong.

last updated 41 week of 2026