Data 360 Technical Architect

Our client is searching for a highly technical, hands-on Salesforce Data 360 Technical Architect to lead the data engineering, complex integrations, and custom development within our Data 360 ecosystem. While the Solution Architect defines the overarching data strategy and modeling, you will be responsible for the exact technical execution. You will build high-volume ingestion pipelines, write advanced SQL for complex transformations and Calculated Insights, configure Zero Copy integrations, and implement the technical foundations for Agentforce and AI-driven workflows. You are the ultimate technical escalation point for optimising data processing and system performance., * Data Engineering & Transformation: Write, optimise, and troubleshoot highly complex SQL queries for batch and streaming data transformations, custom Calculated Insights, and complex segmentation logic.

• API & Integration Development: Implement and manage Data 360 Ingestion APIs, Streaming APIs, and Web/Mobile SDKs to capture high-velocity, Real Time behavioral data from external applications.
• AI & Unstructured Data Pipelines: Engineer pipelines for unstructured data, configuring vector embeddings, chunking strategies, and Retrieval-Augmented Generation (RAG) architectures to power Agentforce.
• Extensibility & Activation: Develop custom Salesforce Core solutions (Apex, Flow, Platform Events) to trigger Real Time actions and build custom Data Action Targets leveraging external webhooks.
• Platform Performance & Security: Own the technical governance of the platform, optimising query performance, managing identity resolution edge cases, and ensuring strict adherence to OAuth protocols, row-level security, and data encryption standards.

• Experience: 3+ years of data engineering or technical architecture experience, with a minimum of 2 years of deep, hands-on configuration and development specifically within Salesforce Data 360 (Data Cloud).
• SQL Mastery: Expert-level proficiency in ANSI SQL, including advanced analytical functions, window functions, and query optimization for large-scale data sets.
• Salesforce Development: Strong hands-on coding experience on the core Salesforce platform, specifically with Apex, SOQL, and Platform Events .
• API Architecture: Deep understanding of RESTful APIs, JSON, OAuth 2.0 flows, and webhook architecture for managing high-volume data payloads.
• Identity & Data Modeling: Deep technical understanding of the Customer 360 Data Model, complex Identity Resolution rulesets, and Data Lakehouse architectures.

Optional Skills

• External Data Platforms: Hands-on experience with external data environments often federated with Data 360, such as Snowflake, Databricks, Amazon Redshift, or Google BigQuery.
• Advanced AI Integration: Experience configuring Bring Your Own Model (BYOM) integrations via Amazon SageMaker, Databricks, or Google Vertex AI.
• Integration Middleware: Proficiency with MuleSoft (Anypoint Platform) for API-led connectivity and complex ETL/ELT orchestration.
• Scripting Languages: Working knowledge of Python, PySpark, or Node.js for external data preparation or serverless function execution (eg, AWS Lambda).