Role: Senior Data Engineer – Snowflake, Couchbase, MuleSoft & Adobe Journey Optimizer
Position Type: Full-Time Contract (40hrs/week)
Contract Duration: Long term contract
Work Hours: US Time
Work Schedule: 8 hours/day (Mon-Fri)
Location: 100% Remote (Candidates can work from anywhere in LATAM Countries)
We are seeking a Senior Data Engineer to design, build, and optimize scalable data pipelines, integration frameworks, and foundational data architecture across a modern customer and enterprise data ecosystem. This role will work predominantly in Snowflake and Couchbase, with key integrations being through MuleSoft and Adobe Journey Optimizer. The ideal candidate combines strong hands-on engineering depth with sound architectural thinking, a product mindset, a bias for automation, and an AI-forward approach to designing intelligent, future-ready data solutions.
Key Responsibilities
• Design, develop, and maintain robust batch and near-real-time data pipelines across Snowflake, Couchbase, and connected enterprise platforms.
• Define and contribute to target-state data and integration architecture, including platform patterns, data flow design, interface contracts, and scalability considerations across enterprise systems.
• Build and optimize scalable data models, ingestion frameworks, and transformation pipelines to support analytics, operational use cases, personalization, and downstream integrations.
• Partner with Mulesoft and Adobe Journey Optimizer and broader marketing technology teams to enable high-quality, timely, and governed data flows that support audience activation, journey orchestration, and customer engagement.
• Engineer and maintain data structures for structured and semi-structured data, including JSON and event-based payloads, with a focus on quality, lineage, observability, and performance.
• Proficiency with MDM (or other data cleansing tools)
• Optimize Snowflake performance, scalability, and cost efficiency through thoughtful warehouse design, workload tuning, partitioning strategies, and effective data lifecycle management.
• Support Couchbase data design and integration patterns for operational, low-latency, and document-based workloads.
• Evaluate architectural tradeoffs across batch, streaming, API, and event-driven patterns to ensure solutions are secure, resilient, maintainable, and aligned to enterprise standards.
• Implement data quality controls, reconciliation processes, monitoring, and alerting to ensure reliability and trust in enterprise data assets.
• Collaborate with product, CRM, marketing, architecture, and engineering stakeholders to translate business requirements into scalable technical solutions and reference designs.
• Establish and promote engineering standards for CI/CD, testing, version control, documentation, security, and reusable integration patterns.
• Identify opportunities to apply AI, machine learning enablement, and intelligent automation to improve data engineering workflows, operational efficiency, and business outcomes.
• Serve as a senior technical contributor and mentor, helping raise engineering standards and guiding best practices across the team.
Required Qualifications
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience.
• 7+ years of experience in data engineering, integration engineering, platform engineering, or solution architecture roles in enterprise environments.
• Strong hands-on expertise in Snowflake, including data modeling, SQL development, performance tuning, security, and workload optimization.
• Experience working with Couchbase or similar NoSQL/document databases in production environments.
• Experience designing and supporting MuleSoft integrations, APIs, and data transformation patterns using enterprise integration best practices.
• Hands-on experience supporting data integration for Adobe Journey Optimizer, Adobe Experience Platform, or similar customer data and journey orchestration platforms.
• Strong understanding of data architecture, integration architecture, and distributed system design, including tradeoffs across batch, API, event-driven, and near-real-time patterns.
• Experience creating scalable technical designs, solution patterns, and architecture documentation for enterprise data platforms and integrations.
• Strong proficiency in SQL and at least one modern programming or scripting language such as Python, Java, or JavaScript.
• Experience with REST APIs, event-driven architectures, JSON payloads, and integration troubleshooting across distributed systems.
• Knowledge of data governance, data quality, observability, privacy, and secure handling of enterprise and customer data.
• Strong communication skills with the ability to work across technical and business teams and influence solution design.
Preferred Qualifications
• Experience with Adobe Experience Platform schemas, identity concepts, datasets, segmentation support, or event ingestion patterns.
• Experience with modern orchestration, DevOps, and automation practices including CI/CD pipelines, Git-based workflows, infrastructure automation, and test automation.
• Familiarity with streaming or near-real-time architectures and related technologies.
• Experience supporting customer 360, CRM, loyalty, personalization, or digital engagement use cases.
• Knowledge of cloud-native architecture patterns, reference architecture development, and enterprise data platform design.
• Experience contributing to architecture reviews, non-functional requirement definition, and platform roadmaps.
• Relevant certifications in Snowflake, MuleSoft, Adobe Experience Platform, or cloud platforms are a plus.
AI-Forward Mindset
We are looking for someone who actively embraces AI as a core part of modern engineering. This person should be curious about how generative AI, intelligent automation, and emerging platform capabilities can improve developer productivity, strengthen data quality, accelerate delivery, and unlock new business value. The right candidate will evaluate AI-enabled tools pragmatically, design data foundations that are AI-ready, and help the organization adopt scalable, secure, and responsible approaches to AI-powered data and integration solutions.
Success Profile
• Thrives in complex, cross-platform environments and can balance strategic thinking with hands-on execution.
• Brings strong ownership, sound judgment, and a continuous improvement mindset.
• Understands how to engineer for scalability, maintainability, resilience, and business impact.
• Can bridge the gap between data platforms, operational systems, and customer engagement technologies.
• Acts as a force multiplier through mentorship, documentation, and reusable engineering practices.
