Senior Data & AI Platform Engineer

Workiva

Senior Data & AI Platform Engineer at Workiva responsible for the build, operation, security, and optimization of the Enterprise Data Platform. Collaborating with various teams to implement robust data controls and support AI applications.

Posted 7/31/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $111,000 - $178,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing Snowflake platform infrastructure, implementing data mesh principles, and optimizing data workflows. Proficient in SQL query tuning, RBAC management, and utilizing tools like dbt, Airflow, and Atlan for data governance and integration.

Highest-signal resume keywords

Snowflake Platform Infrastructure ManagementSQL Query TuningData Mesh ImplementationRBAC ManagementPython Scripting for Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQL Query TuningSnowflake Account AdministrationDbt (Core or Cloud)RBAC ManagementModel Context Protocol (MCP)Data Cataloging ToolsAirflowFivetranWorkatoAWS Data Infrastructure

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationCollaborationMentoring

Tools & Technologies

SnowflakeAtlanQuickSightSigmaTableauAirflowFivetranWorkato

Certifications & Qualifications

SnowPro Core CertificationSnowPro Advanced Certification

Industry Keywords

Data EngineeringPlatform EngineeringData Mesh PrinciplesFedRAMPSOX ComplianceAgile/Sprint Environment

Tech Stack

Tools & technologies

AirflowAWSCloudPythonSQLTableau

About the role

Key responsibilities & impact

Build and maintain Snowflake platform infrastructure: Configure and operate warehouses, resource monitors, query tags, replication, account parameters, and advanced features (such as Iceberg, External Access Integration, and compute pools)
Implement data mesh boundaries: Build and support dbt Mesh patterns and domain boundaries across business functions (Finance, Marketing Ops, CPX, etc.)
Maintain RBAC permission models, service-user provisioning, solution-owner access patterns, and least-privilege enforcement in partnership with Okta and App Cafe
Operate and optimize integration patterns for orchestration (Airflow), ingestion (Fivetran), operational tools (Workato, Salesforce), and ELT workflows within established guardrails
Drive best practices for naming conventions, schema/database layouts, environment promotion patterns, and code reviews across data teams
Implement Snowflake data access patterns for LLM pipelines, semi-structured data consumption, context retrieval, and feature store integrations in partnership with AI/ML teams
Deploy and manage Model Context Protocol (MCP) servers that safely expose governed Snowflake data to AI agents and LLM applications
Maintain evaluation pipelines and test suites to validate agent accuracy, detect hallucination risks, and verify data domain coverage before production release
Partner with GRC and Security to execute FedRAMP boundary controls, field-level masking, data sanitization, and schema security reviews
Operate and integrate Atlan for enterprise data cataloging, column-level lineage, and lakehouse metadata governance
Drive cost visibility using query tags, warehouse sizing optimizations, and showback alignment with business departments
Enable BI tools (QuickSight, Sigma, Tableau, etc.), analyst personas, and developer workflows through performance tuning and access guidance
Participate in design reviews, conduct pull request reviews, and mentor mid-level/junior engineers on data platform standards and dbt patterns

Requirements

What you’ll need

5+ years of relevant experience in data engineering or platform engineering
2+ years of hands-on experience managing or operating Snowflake platform infrastructure
Bachelor’s degree in Computer Science, Engineering, Math, Statistics, Finance, or a related discipline, or equivalent practical experience
Proven hands-on experience with SQL query tuning, Snowflake account administration/RBAC, and platform automation
Strong hands-on experience with dbt (Core or Cloud), dbt Mesh, and data mesh principles across enterprise domains
Hands-on experience with Snowflake RBAC, row/column masking, secure views, data cataloging tools (Atlan), and compliance standards (FedRAMP, SOX, or equivalent)
Familiarity or hands-on experience with Model Context Protocol (MCP), LLM data retrieval pipelines, vector/semantic search patterns, or Cortex automation
Strong scripting skills in Python for platform automation; working knowledge of AWS data infrastructure (S3, IAM, Secrets Manager)
Experience with Airflow, Fivetran, Workato, and enterprise BI tools (QuickSight, Sigma, Tableau, Omni)
Demonstrated experience analyzing query logs, tuning warehouse configurations, and optimizing cloud compute costs
SnowPro Core or Advanced certification
Strong written and verbal communication skills to partner effectively across engineering, security, and business analyst teams
Ability to work effectively in an Agile/Sprint environment, translating technical tasks into clean, well-documented deliverables
Collaboration: Track record of working cross-functionally and helping elevate team-wide engineering practices through peer mentoring and code reviews

Benefits

Comp & perks

A discretionary bonus typically paid annually
Restricted Stock Units granted at time of hire
401(k) match and comprehensive employee benefits package