Lead Analytics Engineer
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Job Description
Lead Analytics Engineer modernizing SavATree’s enterprise data and analytics capabilities. Building governed Snowflake, Databricks, and dbt products, internal tools, and AI-enabled workflow automations.
Responsibilities:
- Discover user workflows and identify the decision or action behind requests
- Define requirements, business rules, ownership, data dependencies, and acceptance criteria
- Create product and technical roadmaps, sequence dependencies, and maintain the delivery backlog
- Select system boundaries, architecture, data contracts, and user experiences
- Build governed dbt models, analytical experiences, tests, and AI-assisted automations
- Validate source data, business rules, user acceptance, and quality
- Deploy, support, document, measure adoption, and continuously improve products
- Retire redundant legacy workflows and dashboards after replacements are accepted
- Meet with office managers, arborists, branch leaders, regional leaders, and executives to understand operational workflows
- Build production-grade staging, intermediate, fact, dimension, and metric models in dbt
- Model CRM, ERP, operational, historical, and third-party enterprise data
- Implement freshness checks, documentation, lineage, observability, and GitHub CI/CD
- Investigate discrepancies and reconcile results across operational systems, Snowflake, Databricks, dbt, Finance, and analytical products
- Build scorecards, governed datasets, analytical workflows, alerts, and lightweight internal tools
- Prototype and deliver focused internal experiences using Replit or comparable AI-enabled tools
- Automate analytical, governance, operational, and engineering workflows using Python, SQL, orchestration tools, and AI agents
- Inspect application entities, tables, columns, relationships, lifecycles, calculated fields, customizations, and business rules
- Map approved business requirements to source entities and fields
- Validate replicated application data for completeness, accuracy, timeliness, and analytical fitness
- Identify and build AI-assisted internal tools, agents, and human-in-the-loop workflows
- Evaluate emerging AI capabilities and translate promising ideas into controlled production experiments
- Deliver roadmap milestones including governed models, reconciliation reporting, internal applications, AI workflows, and a certified core metric layer
Requirements:
- 7+ years of progressively responsible experience across data engineering, analytics engineering, software engineering, or data products
- Advanced production experience with SQL, Snowflake, and dbt, including modeling, testing, documentation, lineage, and deployment
- Databricks experience strongly valued
- Demonstrated ownership of products from stakeholder discovery through roadmap, build, deployment, validation, and support
- Practical Python experience for analysis, automation, integration, and lightweight application development
- Ability to create internal tools and workflows without requiring a separate engineering team for every prototype
- Strong Git and GitHub practices, including pull requests, reviews, automated testing, and CI/CD
- Experience with CRM, ERP, field-service, billing, or comparable transactional-system data
- Ability to communicate with frontline business users and senior technical stakeholders
- Evidence of independent execution across ambiguous technical and organizational boundaries
- Experience with Microsoft technologies such as Dynamics 365, Azure, Fabric, or Power Platform preferred
- Hands-on Databricks experience, including lakehouse design, Delta tables, notebooks, jobs, or Unity Catalog preferred
- Sigma Computing experience preferred
- Experience with Replit or similar AI-enabled application platforms preferred
- Experience with AI agents, retrieval-augmented generation, tool use, workflow orchestration, or agent evaluation preferred
- Experience with semantic layers, metrics-as-code, data contracts, data observability, and warehouse cost optimization preferred
- Experience in distributed, multi-location, field-service, or operationally complex businesses preferred
Benefits:
- Annual bonus
- Full-time, permanent, exempt employment
- Remote work arrangement
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