Salesforce Data 360 Engineer

Who We Are

HIKE2 is an advisory and innovation partner helping organizations design and build what’s next.

We work with complex and regulated industries, including law firms, financial services, insurance, professional services, and high-growth SaaS companies, to modernize operating models and embed data, automation, and AI into the core of how work gets done.

Our clients aren’t just upgrading technology. They are rethinking workflows, activating governed AI, and designing environments where humans and intelligent systems work side by side.

We believe meaningful transformation happens when strategy, data, design, and engineering move together. Siloed initiatives don’t scale. Real progress requires clarity of vision, strong data foundations, responsible governance, and disciplined execution.

Our teams bring deep industry expertise, human-centered design, and advanced data and cloud capabilities to architect secure, scalable solutions built for real-world complexity. From modern data platforms to AI-enabled workflows and enterprise automation, we help organizations move from experimentation to measurable impact.

We thrive in change and move from blank slate to working systems. We care deeply about outcomes, trust, and building long-term partnerships.

We don’t just implement technology. We help design the future of work.

Role Description:

A Salesforce Data 360 Engineer builds and manages data pipelines, unifies customer data, and connects external sources to the Salesforce Data Cloud platform

Key Responsibilities:

• Data Ingestion: Connect and ingest data from CRM, marketing platforms, cloud data warehouses, and external APIs into Salesforce Data Cloud.

• Data Modeling: Create and manage Data Model Objects (DMOs), Data Lake Objects (DLOs), and standard or custom mappings.

• Identity Resolution: Set up and optimize identity resolution rules to merge duplicate customer profiles into a single, unified view.

• Data Activation: Build segments and activate unified data across marketing, sales, and service channels.

• Monitoring & Troubleshooting: Monitor data streams, troubleshoot ingestion errors, and ensure data quality and compliance.

• Collaboration: Work with administrators, marketers, and developers to align data architecture with business goals.