Sr. AI & Data Engineer

Hybrid role in Irving, TX (3 days per week in the office) where you will help design and operate modern, cloud-native Snowflake AI Data Cloud solutions. Accenture’s Sr. AI & Data Engineer role blends governed data engineering with production-ready agentic AI, including RAG pipelines and LLMOps practices that support reliable, auditable AI behavior.

What you’ll do

• Architect and maintain a scalable, governed Snowflake AI Data Cloud environment, covering compute optimization, warehouse sizing, and cost management.
• Design and implement ELT/ETL ingestion frameworks using Snowflake SQL, Snowpark (Python), Dynamic Tables, Streams, Tasks, and Snowpipe for batch, streaming, CDC, and event-driven patterns.
• Create reusable, AI-ready data products with clear ownership, semantic context, data quality SLAs, and lineage tracking.
• Apply enterprise security controls including RBAC/ABAC, column- and row-level security, dynamic data masking, classification tags, and audit logging.
• Integrate Snowflake with upstream systems, dbt and Apache Airflow orchestration, governance tools, and downstream analytics consumers.
• Build multi-step agentic AI workflows using Snowflake Cortex Agents, Cortex AI Functions, Cortex Search, and Cortex Analyst.
• Develop production-grade RAG pipelines using vector search, semantic retrieval, and hybrid search over governed Snowflake datasets.
• Implement tool-use orchestration, prompt engineering, and evaluation frameworks (LLMOps) to support reliable and auditable agent behavior.
• Use agentic automation for operational use cases including anomaly detection, data quality remediation, query diagnosis, documentation generation, and incident summarisation.
• Connect AI agents to enterprise systems via MCP (Model Context Protocol) connectors, REST APIs, and event-driven messaging architectures.
• Enforce data modeling standards such as Kimball dimensional and 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.

What you bring

• 3+ years of professional data engineering experience, including building agentic AI or LLM-powered applications in an enterprise context (RAG pipelines, tool-use agents, prompt engineering).
• 3+ years of Snowflake-native experience: Snowpark (Python), Dynamic Tables, Streams & Tasks, Snowpipe, the Cortex AI suite, and performance tuning.
• 3+ years of Python experience (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.

Skills and tools

Snowflake, Snowflake AI Data Cloud, Snowflake SQL, Snowpark (Python), Dynamic Tables, Streams, Tasks, Snowpipe, Snowflake Cortex Agents, Cortex AI Functions, Cortex Search, Cortex Analyst, RAG, vector search, semantic retrieval, hybrid search, LLMOps, Python, SQL, RBAC, ABAC, dynamic data masking, REST APIs, MCP (Model Context Protocol), dbt, Apache Airflow, Kimball dimensional, Data Vault 2.0, BI tools.

Benefits

• Medical, dental, vision, life, and long-term disability coverage
• 401(k) plan
• Bonus opportunities
• Paid holidays
• Paid time off
• Reasonable range of compensation (varies by office location, role, skill set, and level of experience)

Compensation and locations

Salary range: USD 59,100 - 205,800 per year. This hybrid role requires three days per week in the office across locations including Dallas, TX; Houston, TX; Columbus, OH; Atlanta, GA; Tampa, FL; Irving, TX; and St. Petersburg, FL.

Role location salary ranges include California $70,350 to $205,800; Colorado $63,800 to $177,800; Connecticut $63,800 to $177,800; District of Columbia $68,000 to $189,300; Illinois $59,100 to $177,800; Maine $54,400 to $151,400; Maryland $63,800 to $177,800; Massachusetts $63,800 to $189,300; Minnesota $63,800 to $177,800; New York $66,300 to $205,800; New Jersey $68,000 to $205,800; Ohio $59,100 to $164,600; Virginia $59,100 to $189,300; Washington $80,200 to $189,300.

Preferred qualifications

• 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 (object storage, IAM, networking, managed compute)
• Experience implementing data governance, security policies, and compliance frameworks on cloud data platforms
• Snowflake SnowPro Advanced certification (Data Engineer or Architect) or Cortex AI practitioner credentials
• Experience with vector databases (e.g., Snowflake Vector Search, Pinecone, Weaviate) and embedding models (e.g., Snowflake Arctic Embed)
• Hands-on experience with MLOps tooling: model registries, evaluation pipelines, experiment tracking, and monitoring in production
• Familiarity with MCP and enterprise agentic control plane architectures
• Exposure to streaming technologies (Apache Kafka, Kinesis) integrated with Snowflake ingestion pipelines