Director of Engineering (Data & Platforms)

Essintial Enterprise Solutions LLC•Hampden Township, PA

1d•$120,000 - $150,000

About The Position

Essintial is investing in a multi-year modernization of how data, inventory, and business insights come together. The center of this transformation is a modernized data and operations hub. The Director of Engineering (Data & Platforms) will stand up a Microsoft Azure data warehouse (Fabric or Databricks) to give the business live billing, inventory, and KPI visibility. In parallel, Essintial is centralizing its systems of record: extending Salesforce Service Cloud as the operational heart for projects and inventory, and introducing a modern WMS. This hire will own the technical planning and architecture behind that work. They will lead a small, hands-on existing engineering team and deliver a unified technical estate where Azure data and Salesforce + WMS work as one. The Director of Engineering (Data & Platforms) is a player-coach who designs, builds, and runs Essintial’s core technical platforms. They are first and foremost an Azure Data and ELT specialist. They will deliver a governed Azure analytics layer (Microsoft Fabric or Databricks) that powers billing, operations, and executive decision-making, and unify the existing client-integration estate onto a single ELT pattern. They will also lead the modernization of operational data: centralizing inventory and project data in Salesforce and implementing warehouse management that scales across the national network. They inherit an established Azure integration estate, a decade of Service Cloud, a Senior Data Engineer already shipping, and a strategy on the path forward. They will set engineering cadence, and be accountable for outcomes the business can measure.

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: 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.

Nice To Haves

WMS experience very much preferred
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.
WMS delivery is highly preferred.

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.