Director of Engineering (Data & Platforms)

Essintial Enterprise Solutions LLC•Palmetto, FL

1d•$120,000 - $150,000

About The Position

Essintial is a national IT operations partner that provides technology services to retail, restaurant, and enterprise brands. The company is undergoing a multi-year modernization of its data, inventory, and business insights systems, centered around a modernized data and operations hub. This role will be responsible for establishing a Microsoft Azure data warehouse (Fabric or Databricks) to provide live visibility into billing, inventory, and KPIs. Additionally, the role will involve centralizing systems of record by extending Salesforce Service Cloud for project and inventory management and introducing a modern Warehouse Management System (WMS). The Director of Engineering (Data & Platforms) will lead the technical planning and architecture for this transformation, managing a small, existing engineering team. The goal is to create a unified technical estate where Azure data and Salesforce + WMS function seamlessly together. This is a player-coach role focused on designing, building, and running Essintial’s core technical platforms, with a strong emphasis on Azure Data and ELT expertise. The position will deliver a governed Azure analytics layer to support business decision-making and unify client integrations onto a single ELT pattern. It also includes modernizing operational data by centralizing inventory and project data in Salesforce and implementing a scalable WMS. The role inherits an established Azure integration estate, a decade of Service Cloud experience, a Senior Data Engineer, and a defined strategy. The Director will establish engineering cadence and be accountable for measurable business outcomes.

Requirements

Hands-on Microsoft Azure Data: 8+ years in data engineering, with deep production experience in Fabric, Databricks, or Synapse. Expertise in Medallion architecture, orchestration, and governance. Gold models that a semantic layer or analytics platforms can consume.
ELT and Integration: Proven track record landing multi-client SaaS and API feeds into a shared ELT pattern (not one-off pipelines), plus Salesforce and enterprise API integrations.
Salesforce in production: Experience with Service Cloud (or equivalent): data modeling, integrations, and release management for programs used by operations.
WMS or inventory platform delivery: (Very much preferred). Experience with serialized parts, barcode receiving, multi-warehouse/3PL, and RMA.
Leadership: 3+ years leading engineers in a player-coach model. Established delivery practice (backlog, sprint, review, release).
Technical Stack: Microsoft Fabric or Databricks, ADF, Service Bus, and Functions. Strong SQL (T-SQL), Python/PySpark, and C# (.NET). KQL for platform operations.
Excellent communication with warehouse, PMO, finance, and executive stakeholders.
Bachelor’s degree in Computer Science, Engineering, or equivalent professional experience.
Demonstrated delivery of an enterprise data warehouse is required; WMS delivery is highly preferred.

Nice To Haves

Microsoft Fabric and/or Databricks certifications.
Hands-on experience with Salesforce-native WMS/ERP.
Salesforce Revenue Cloud / order-to-fulfillment.
Field-service or logistics domain: multi-site retail/restaurant, POS, audit-sensitive serials.

Responsibilities

Lead the Azure data platform strategy: Design and operate the Fabric and/or Databricks environment (OneLake / ADLS, Data Factory, Service Bus, Functions). Join warehouse movements, client feeds, and Service Cloud contracts in a single governed Gold layer.
Unify client ELT: Standardize the existing client integrations onto one landing, transform, and error-handling pattern. New clients reuse the platform.
Own technical delivery of the modernization roadmap. Convert executive strategy into a prioritized backlog that ships on a regular cadence.
Own the Salesforce WMS program: Lead data modeling, vendor selection, implementation, and cutover. Partner with Depot leadership on receiving, cycle counts, kitting, serialized controls, and audit readiness.
Preserve Service Cloud as the operational hub for projects and dispatch. Model SOWs and deliverable templates as Salesforce data to avoid named-user field-service licensing traps.
Manage the engineering team. Install planning, sprint, review, and release discipline.
Direct vendors and implementation partners on time-boxed outcomes. Retain architectural ownership of both Azure and Salesforce.
Replace manual reconciliations with API-level integrations across billing, inventory, technician records, and project status.
Apply AI where it improves operations: image review at capture, structured extraction of contract rules, and natural-language status for PMs and executives.
Own security, reliability, and cost across the technical environment (Azure governance and Salesforce sandbox/profile discipline).
Report progress in operational terms: dock-to-stock, billable vs complete, sites live, serial accuracy.