Accenture

Forward Deployed Technical Consultant-Snowflake

Accenture$90K — $140K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in a related field or equivalent education
  • 3 years of hands-on experience with Snowflake AI Data Cloud and large-scale data projects
  • 1 year of experience in designing and implementing agentic AI solutions in production
  • 1 year of production experience with various AI platforms alongside Snowflake Cortex AI
  • 5 years of programming experience, preferably in Python or Java
  • 2 years of production experience in CI/CD and MLOps/LLMOps practices

Responsibilities

  • Design enterprise-ready AI agents and workflows
  • Construct Snowflake data pipelines using advanced Snowflake features
  • Integrate GenAI capabilities into existing workloads using Cortex AI
  • Optimize data models and queries for efficiency and cost-effectiveness
  • Deploy tailored AI applications across various industries
  • Build Snowflake-native pipelines and ensure operational efficiency
  • Manage MLOps and LLMOps pipelines with continuous integration and delivery

Benefits

  • In-office presence required 3 days per week at the local office
  • Opportunity to work with global enterprise teams
  • Engage in high-impact projects across diverse industries
  • Collaborative work environment focused on cutting-edge technology
  • Access to professional development and skill enhancement programs
Full Job Description
You Are

A Forward Deployed Technical Consultant with strong experience building data solution workloads on the Snowflake AI Data Cloud. You partner closely with clients to design, build, and implement modern data solutions on Snowflake, ensuring data quality, performance, and cost-efficiency, and you act as a trusted technical advisor helping customers harness their data, drive insights, and power AI initiatives.

The Work

You will embed directly with clients as both technologist and trusted advisor. You will partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains.

Responsibilities
  • Design enterprise-ready AI agents: retrieval, orchestration, tool invocation, evaluation harnesses.
  • Build Snowflake data pipelines with Dynamic Tables, Streams, and Tasks; use Snowsight UI for query authoring, dashboards, and operational visibility. • Build GenAI capabilities into Snowflake workloads with Cortex AI (Cortex Search, Cortex Analyst, Cortex LLM functions).
  • Optimize data models, queries, and processing workflows on Snowflake for performance and cost.
  • Process large-scale data on Snowflake with SQL, Python, and the Spark ecosystem.
  • Tailor and deploy agentic applications across finance, healthcare, and retail; conduct workshops, PoCs, and code-with sessions with clients. • Define and use metrics for agent accuracy, latency, safety, and cost.
  • Build Snowflake-native pipelines using Cortex AI, Dynamic Tables, and the Snowflake data ecosystem.
  • Operate MLOps / LLMOps pipelines with CI/CD across the ML and LLM lifecycle.
  • This role requires in-office presence in the local ATC office 3 days per week.


Here's What You Need:
  • Bachelor's degree or completion of a college program in a related discipline
  • 3 years of experience on the Snowflake AI Data Cloud and large-scale data projects (Snowpark, Dynamic Tables, Streams & Tasks, Snowsight). You've also built API layers that expose data and AI/ML capabilities to enterprise systems.
  • 1 year experience in designing and shipping agentic AI solutions in production.
  • 1 year experience in shipping agentic solutions in production (agents, orchestration, context based solutions, RAG, workflows) using AI platforms (OpenAI, Claude, Vertex AI, open source) and Snowflake Cortex AI (Cortex Search, Cortex Analyst, Cortex LLM functions).
  • 5 years of experience in Python, Java, or equivalent. Comfortable with evaluation tooling, logging, monitoring, and observability.
  • 2 years' experience in shipping to production: CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging. Practical MLOps and LLMOps experience across the ML and LLM lifecycle (model training, serving, monitoring, prompt management).

English is required for this position as this role will be aligned to multi-national teams where English is the common language across our Global Enterprise. Due to the significant high volume of interactions with these English-speaking multi-national teams, which is inherent to this position, it is not possible to reorganize the company's activities to avoid this requirement.

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location,role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation, based on full-timeemployment, for roles that may be hired as set forth below.

The recruiting efforts for this position are intended to fill a brand-new position. The base pay range shown below is intended as a guideline to reflect the majority of offers for this role.

It does not represent a maximum limit - in some cases, actual compensation may exceed the range where appropriate."

Information on benefits is here:

Role Location Annual Salary Range

British Columbia/Ontario $90,850 to $140,850

About Accenture

Accenture plc is a multinational professional services company that provides services in strategy, consulting, digital, technology, and operations. The company has more than 537,000 employees serving clients in more than 120 countries. Accenture operates across five business segments: Communications, Media & Technology; Financial Services; Health & Public Service; Products; and Resources. The company is headquartered in Dublin, Ireland, and has offices worldwide.
Learn more about Accenture
Size
624,000 employees
Market Cap
$173.8 billion
Industry
Net Income
$5.2 billion
Founded
1989
5 Year Trend
+11.2%
Revenue
$44.7 billion
NASDAQ

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