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Senior Salesforce Integration and Data Engineer - Hybrid,In Person Interview

MSys Inc.

Phoenix, AZ · HybridJobSeen todaySeen in employer's feed today

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At a glance

Compensation
No compensation found
Location
Phoenix, AZHybrid
Work Authorization
Not specified

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Job overview

The senior Salesforce Integration and Data Engineer will lead a digital transformation by decommissioning legacy SQL layers and building direct, scalable integration paths to Salesforce, ensuring data integrity, low latency, and optimal API usage across real‑time and batch pipelines.

Skills & qualifications

RequiredNice to have

Skills

Salesforce IntegrationSQLRESTSOAPMuleSoftDell BoomiCeligoAzure Data FactoryApexLightning Web ComponentsData MappingETLAPIData Governance

Full job description

In Person Interview Long term project Linkedin MustHybridLocal candidates only*

Job Description:

We are seeking a highly skilled Senior Salesforce Integration & Data Engineer to lead a critical digital transformation project. In this role, you will be responsible for decommissioning our legacy SQL database intermediate layer and replacing it with direct, modern integration paths between our core source systems and Salesforce. The ideal candidate will bridge the gap between traditional database architecture and modern cloud ecosystems. You will design, build, and maintain highly scalable real-time and batch integration streams, ensuring data integrity, minimal latency, and optimal API footprint management.

Core Responsibilities 1. Integration & Pipeline Re-architecting

  • Decommission Legacy SQL Layers: Analyze and phase out existing intermediate SQL relational databases currently functioning as staging layers between source systems and Salesforce.

  • Establish Direct Connections: Architect, develop, and deploy robust direct APIs (REST/SOAP) and event-driven patterns to connect upstream source systems directly to Salesforce.

  • Middleware Management: Configure and maintain integration platforms or middleware (e.g., MuleSoft, Dell Boomi, Celigo, or Azure Data Factory) to manage traffic, data orchestration, and transformation rules.

  1. Data Governance & Architecture
  • Data Mapping & Transformation: Rewrite complex SQL stored procedures, views, and ETL logic into scalable Apex, middleware logic, or declarative Salesforce flows.

  • Large Data Volume (LDV) Strategy: Design data models within Salesforce that handle high volumes without degrading system performance, incorporating indexing and custom skinning where necessary.

  • Error Handling & Reconciliation: Build end-to-end exception logging and data reconciliation mechanisms to identify and resolve synchronization failures automatically.

  1. Platform Development & Optimization
  • Custom Development: Write clean, asynchronous, and well-tested Apex code, Triggers, and Lightning Web Components (LWC) when custom programmatic solutions are needed for data intake.

  • Governor Limits Optimization: Guard the Salesforce environment against API throttling, row-locking issues, and governor limit breaches by implementing optimal batching and queuing strategies.

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