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Location
Remote (LATAM)
Seniority
Senior · 7+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 14, 2026. First seen by Alion on Nov 13, 2026. InAllMedia scores A on the Alion truth index.

Overview
Company
Impact
Profile match
InAllMedia is a technology and design services firm that builds software for international clients with remote, distributed engineering teams located across Latin America. The company runs a community of vetted engineers called Coderfull, reports more than 4,000 experts in its network with over 500 assigned long term, and provides custom development, UX and UI design, quality engineering, cloud and DevOps, data and Salesforce work, including work for a large American streaming client. It hires full-stack, backend and data engineers, AI agent developers, Salesforce developers and architects, QA engineers, UX and UI designers, DevOps engineers, business analysts and technical recruiters.

Senior Salesforce Engineer - Performance & Data Cloud

Position: Senior Salesforce Engineer - Performance & Data Cloud

Location: Remote from LATAM

Contract Type: Full-time vendor (Contract directly with In All Media)

Time Zone Alignment: To be confirmed

About In All Media

In All Media is a global technology and design firm focused on building impactful digital solutions through remote, distributed teams across LATAM.

We partner with international clients across industries, providing long-term technical expertise, product innovation, and team augmentation.

Contract Details: This is a 100% remote contractor position open to talent anywhere in LATAM. Your contract and engagement will be directly managed with In All Media.

Project Overview

Our client is a global online recruitment and career marketplace platform connecting millions of job seekers with employers worldwide through high-volume, enterprise-scale cloud architectures.

This role is embedded within the client's core enterprise CRM and customer data platform engineering organization, focusing on stabilizing, scaling, and optimizing complex Salesforce Core and Salesforce Data Cloud environments supporting tens of millions of records, thousands of internal users, and high integration throughput.

The engineer will lead critical performance optimization and platform stability initiatives, including resolving Apex and SOQL bottlenecks, eliminating row-lock contention, managing large data volumes (LDV), and remediating data skew across high-concurrency environments.

A significant part of the role involves strengthening production Salesforce Data Cloud operations by optimizing ingestion pipelines, identity resolution, data modeling, segmentation, and activation processes while maintaining efficient credit consumption.

The ideal candidate is a deeply hands-on Salesforce engineer with strong expertise in performance diagnostics, asynchronous architecture, large-scale data management, and production Data Cloud engineering. This position requires someone who actively writes and refactors code, rather than a purely advisory or non-coding architect.

Key Responsibilities

  • Apex & SOQL Performance Optimization: Profile, troubleshoot, refactor, and optimize enterprise Apex and SOQL codebases to eliminate row-lock contention, governor-limit exceptions, inefficient queries, and unnecessary code complexity in high-concurrency environments.
  • Trigger & Asynchronous Architecture Modernization: Consolidate and optimize trigger frameworks, improve bulkification, and modernize asynchronous processing using Queueable Apex, Batch Apex, Platform Events, and asynchronous dispatchers. Reduce scheduled job overhead and improve processing reliability.
  • Large Data Volume (LDV) & Data Skew Remediation: Design and execute scalable archiving, purging, and data retention strategies for high-volume Salesforce objects using Big Objects, external archives, and ETL tooling. Identify and resolve parent-child relationship skew and record-ownership skew to improve transactional performance.
  • Salesforce Data Cloud Operations & Optimization: Stabilize production data ingestion streams, optimize Data Lake Object (DLO) and Data Model Object (DMO) architectures, refine identity resolution rulesets, and improve calculated insights, segmentation, and data activation workflows.
  • Data Cloud Credit & Resource Management: Monitor and optimize Salesforce Data Cloud credit consumption, processing efficiency, and resource utilization to support reliable, cost-efficient operations at enterprise scale.
  • Generative AI Performance & Reliability: Diagnose and troubleshoot latency, data grounding, and execution issues across Salesforce Agentforce and Einstein generative AI workflows, improving performance and reliability of AI-driven capabilities.
  • Platform Observability & Production Diagnostics: Leverage Salesforce monitoring and performance tools, including Scale Center, ApexGuru, Proactive Monitoring, and Smart Alerts, to identify performance issues, investigate incidents, and support proactive platform optimization.
  • Platform Hygiene & Release Management: Upgrade outdated Salesforce API, Apex, and Visualforce versions while maintaining compatibility, code quality, and platform stability. Execute deployments through sandbox-first CI/CD pipelines using version control and documented rollback procedures.
  • Technical Documentation & Knowledge Transfer: Develop operational runbooks, document architectural improvements, troubleshooting procedures, and deployment practices, and lead structured knowledge-transfer sessions with internal engineering teams.

Must-Have Skills

  • Experience Level: 5+ years of hands-on Salesforce engineering experience, preferably 7+ years, working with large enterprise Salesforce environments supporting tens of millions of records, thousands of users, and high integration traffic.
  • Active Hands-On Development: Recent, demonstrable experience writing or refactoring Apex code within the last 2-3 years. Candidates focused exclusively on architecture, administration, or technical advisory responsibilities without active coding experience are not a fit.
  • Advanced Apex & Asynchronous Processing: Deep expertise in Apex development, trigger frameworks, bulkification, governor-limit optimization, and asynchronous processing patterns, including Queueable Apex, Batch Apex, and Platform Events.
  • Performance & Contention Diagnostics: Proven hands-on experience identifying, troubleshooting, and resolving row-lock contention, governor-limit exceptions, and SOQL performance bottlenecks in highly concurrent enterprise environments.
  • Large Data Volume (LDV) Management: Strong experience implementing data archiving, purging, and retention strategies, including hands-on remediation of parent-child data skew and record-ownership skew.
  • Production Salesforce Data Cloud: Demonstrated production engineering experience with Salesforce Data Cloud beyond proof-of-concept implementations, including data streams, Data Lake Objects (DLOs), Data Model Objects (DMOs), identity resolution, calculated insights, segmentation, activation, and credit consumption management.
  • Platform Modernization & Release Management: Experience upgrading legacy Salesforce API, Apex, and Visualforce versions while maintaining platform compatibility and stability.
  • Version Control & CI/CD: Hands-on experience managing sandbox-first CI/CD pipelines, source control, release processes, and documented rollback strategies.
  • Salesforce Observability & Monitoring: Practical familiarity with Salesforce performance and monitoring tools such as Scale Center, ApexGuru, Proactive Monitoring, and Smart Alerts, along with issue tracking through Jira.

Nice-to-Have Skills

  • Generative AI & Agentforce Optimization: Experience troubleshooting and optimizing Salesforce Agentforce and Einstein generative AI workflows, including prompt sizing, data grounding, action chains, LLM selection, and performance tuning.
  • Multi-Cloud Enterprise Experience: Experience supporting large-scale Salesforce implementations involving Service Cloud, Computer Telephony Integration (CTI), Omni-Channel routing, or Revenue Cloud.
  • Salesforce Certifications: Relevant certifications such as Salesforce Platform Developer II, Data Cloud Consultant, Data Architect, or Application Architect.

Time Zone & Collaboration

This role requires effective collaboration with distributed engineering teams, internal stakeholders, and enterprise platform specialists.

Candidates must be comfortable participating in technical discussions, troubleshooting production issues, coordinating platform releases, and conducting knowledge-transfer sessions within the team's established working hours.

Specific time zone alignment and required business-hour overlap will be confirmed during the recruitment process.

Language

Candidates must be comfortable communicating technical concepts, documenting engineering solutions, and collaborating with distributed teams in English.

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