About this opportunity
PowerPlan, Inc. lists this Senior Databricks AI Engineer opportunity in smyrna, Georgia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
The Senior AI/ML Engineer will modernize and scale the company’s enterprise data and AI platform by designing AI-ready data models, operationalizing ML systems, and enabling natural-language analytics through Databricks Genie or equivalent AI tooling.
This role exists to shift the organization from dashboard-driven analytics to AI-powered decision intelligence at enterprise scale.
Performance Objectives
Modernize and Operationalize the Analytics Data Platform
Within 6–9 months, design and implement a scalable medallion-based architecture (Bronze/Silver/Gold) in Databricks or Snowflake that supports AI-ready datasets, improves query performance by ≥30%, and reduces data reliability incidents by ≥40%.
Subtasks
Redesign analytical data models for AI/ML consumption
Implement governance using Unity Catalog or Snowflake controls
Establish monitoring and quality validation checkpoints
Within 6 months, establish semantic models and metadata standards that enable business-facing AI querying with ≥95% data trust rating from stakeholders.
Subtasks
Standardize schema design for ML and GenAI workloads
Align business definitions with governed datasets
Implement lineage and access controls
Reduce duplicate or conflicting metric definitions
Build and Deploy Production-Grade ML Pipelines
Subtasks
Standardize MLflow/Feature Store workflows
Implement CI/CD for ML
Improve model observability and drift monitoring
Within 6 months, deploy and optimize Databricks Genie (or equivalent AI query interface) enabling business users to generate accurate plain-language insights with ≥80% adoption across target user groups.
Subtasks
Improve response accuracy through model + metadata tuning
Partner with Product on use-case prioritization
Track and improve AI query accuracy and user engagement
Democratize AI Across Business Teams
Within 12 months, embed AI-driven analytics into at least 3 core business workflows, demonstrating measurable business impact (e.g., cost reduction, revenue lift, or decision cycle time improvement).
Subtasks
Identify high-value AI use cases
Collaborate cross-functionally
Deliver production-ready AI solutions
Document business ROI outcomes
Within 12 months, define and institutionalize architectural standards, best practices, and governance frameworks adopted across Engineering and Analytics teams.
Subtasks
Publish architecture reference patterns
Influence long-term AI strategy
Success Metrics Summary
30%+ performance improvement in analytics workloads
40%+ reduction in data quality incidents
50% reduction in ML deployment cycle time
3+ AI use cases with measurable ROI
≥95% stakeholder trust in AI-generated insights
This is a high-impact platform leadership role enabling enterprise AI transformation. The individual will shape architecture standards, influence executive AI strategy, and lead the shift from traditional BI to AI-powered decision intelligence.
Required Qualifications
10+ years of experience in Data Analytics , Data Engineering , ML Engineering , or AI Engineering
Strong hands-on experience with Databricks or Snowflake in production environments
Expertise in SQL , Python , and distributed data processing (Spark preferred)
Strong understanding of data modeling for analytics and AI
Experience building and deploying ML models in real-world systems
Familiarity with LLMs, GenAI concepts, and AI-assisted analytics
Experience with ML lifecycle tools (MLflow, Feature Stores, CI/CD for ML)
Preferred Qualifications
Direct experience with Databricks Genie or AI-powered BI tools
Experience with Unity Catalog, Delta Live Tables , or Snowflake governance features
Exposure to Azure, AWS, or GCP cloud platforms
Experience working in regulated or enterprise SaaS environments
Ability to explain complex technical concepts to non-technical stakeholders
What Success Looks Like in This Role
Business users can ask questions in plain English and get trusted, accurate insights
Data models are AI-ready, scalable, and well-governed
ML models move smoothly from experimentation to production
Databricks Genie adoption grows with measurable business impact
AI is embedded into analytics not bolted on
Why Join Us
Work on real AI/ML problems at enterprise scale
Influence the evolution of a modern data + AI platform
Partner with senior leaders shaping the company’s AI-first future
Build systems that turn data into decisions not dashboards
PowerPlan is an EOE
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Worksite address
smyrna, GA, 30081, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.