Salesforce Integration Engineer-180626-78

Salesforce Integration Engineer About the Role SageIT Academy is seeking a Salesforce Integration Engineer to strengthen and stabilize how Salesforce participates in the Academy platform. Salesforce is a key system of record, integrated with a Python-based application tier (Flask, FastAPI, Django), a Hasura GraphQL data layer, and other surfaces, all running on AWS (Amazon EKS) with Terraform. The platform is evolving toward an event-driven architecture, and Salesforce needs to consume and react to domain events cleanly and reliably. This role is equal parts integration engineering and platform stewardship. You will diagnose and resolve cross-system data and integration issues, remediate Salesforce defects across Apex, Flows, triggers, and configuration, and help establish sound, repeatable patterns for how Salesforce ingests domain events—reducing anti-patterns and technical debt as the architecture matures. Key Objectives Salesforce integration assessment & event-consumption patterns: Develop a high-level overview of the Academy Salesforce instance to identify anti-patterns and establish a sound, repeatable pattern for consuming domain events into Salesforce. Data synchronization & integrity: Resolve data synchronization issues, object-mapping discrepancies, and record-update conflicts, and close cross-system data-integrity gaps within the Learning Progress domain. Defect triage & remediation: Analyze, triage, and remediate Salesforce defects—including Apex code errors, Flow automation failures, trigger issues, and configuration inconsistencies. Validation & controlled deployment: Perform regression validation and controlled deployment of fixes across environments. Core Responsibilities Assess the current Salesforce instance—objects, automation, integrations, and data flows—and document anti-patterns, risks, and remediation priorities. Design and implement reliable patterns for ingesting domain/business events into Salesforce (platform events, Change Data Capture, inbound APIs, or middleware), favoring decoupled, idempotent, replayable approaches aligned with the platform’s event-driven direction. Investigate and resolve data synchronization failures, object-mapping discrepancies, and record-update / record-locking conflicts between Salesforce and upstream/downstream systems. Diagnose and fix defects across Apex (classes, triggers, batch/async), Flows , validation rules, and configuration; reduce duplicated or conflicting automation. Establish and maintain data-integrity safeguards within the Learning Progress domain—reconciliation, monitoring, and error handling for failed or partial syncs. Write and maintain Apex unit tests and perform regression validation to confirm fixes don’t introduce new issues. Deploy changes in a controlled manner across sandboxes and production using source-driven tooling (SFDX / metadata API, Git-based pipelines, change sets where appropriate). Partner with the Python platform and data teams to align Salesforce integration contracts, event schemas, and error-handling conventions. Document integration flows, mappings, and runbooks for ongoing support. Required Technical Skills 5–8 years of Salesforce development and configuration experience on enterprise orgs. Strong hands-on Apex (classes, triggers, batch/queueable/scheduled async, test classes) and SOQL/SOSL . Proficiency with Flow and declarative automation, and the judgment to know when to use declarative vs. code. Solid experience with Salesforce integration patterns : REST/Bulk/SOAP APIs, Platform Events , Change Data Capture (CDC) , Apex callouts, and webhooks. Demonstrated ability to debug and resolve data synchronization and integrity issues across integrated systems (mapping, deduplication, conflict resolution, reconciliation). Strong defect triage and root-cause-analysis skills across Apex, Flows, triggers, and configuration. Experience with source-driven development and deployment : SFDX, metadata/Tooling API, Git, and CI/CD-based release processes across multiple environments. Understanding of Salesforce data modeling, sharing/security model, and governor limits. Preferred Qualifications Experience with: Event-driven integration to/from Salesforce using a streaming backbone (Kafka, Pulsar, Kinesis) or middleware (MuleSoft, etc.). Integrating Salesforce with Python services and/or a Hasura GraphQL layer. AWS and Kubernetes (EKS) environments; familiarity with Terraform-managed infrastructure. Observability/monitoring of integrations (logging, alerting, dead-letter handling, replay). Salesforce certifications (Platform Developer I/II, Integration Architect, or Administrator). Education / EdTech domain exposure, particularly learner or learning-progress data. Knowledge Of Integration security patterns; OAuth 2.0 and connected apps. Idempotency, retries, and reliable-messaging patterns for cross-system data flows. Data governance, privacy, and compliance requirements. Communication & Collaboration Clear, fluent written and verbal communication—able to explain integration issues, root causes, and fixes to both engineers and non-technical stakeholders. Methodical, evidence-driven troubleshooting and disciplined, low-risk deployment habits. Comfortable working across teams (Salesforce, Python platform, data) in an evolving, event-driven architecture.