Senior Data, Platform & Solutions Engineer

📋 Job Overview

We are looking for a highly experienced, hands-on Senior Data Engineer who can combine deep data engineering expertise with data architecture, cloud platform ownership, and direct client engagement. This is not a traditional back-office data engineering role where you own one pipeline or a narrow piece of a larger platform. You will work directly with clients to understand their needs, recommend the right technical approach, design the architecture, build the solution, and communicate the results.

🏢 About [Company]

Surglobal is a company that values broad technical ownership and client-facing roles, particularly in consulting, startups, or other environments where engineers have had significant ownership rather than operating within one narrow function of a large data organization.

🎯 The Role

You will typically own multiple client projects and operate as both the technical expert and a trusted advisor. The right person is comfortable running a client meeting, discussing architectural trade-offs with technical and business stakeholders, turning those decisions into working solutions, and owning delivery from beginning to end.

✅ Key Responsibilities

• Own the technical delivery of data projects from initial client conversations through architecture, implementation, and ongoing delivery
• Lead client discussions to understand business and technical requirements, ask the right questions, and translate ambiguous problems into clear technical solutions
• Design modern data architectures spanning ingestion, transformation, compute, storage, analytics, and BI layers
• Make informed architecture recommendations based on technical trade-offs, cost, scalability, maintainability, and the client's specific requirements
• Build and maintain production data pipelines, transformations, models, and platform components
• Work hands-on with modern data platforms such as Snowflake, Databricks, BigQuery, and/or Redshift
• Build and maintain transformation workflows using SQL and modern data tooling such as dbt
• Work directly within AWS, GCP, and/or Azure environments, including platform deployment, infrastructure configuration, access and permissioning, and related cloud resources
• Take end-to-end ownership rather than relying on separate infrastructure, architecture, or project-management teams to drive delivery
• Manage multiple client projects simultaneously while maintaining clear priorities, timelines, documentation, and follow-up
• Produce polished client-facing documentation, presentations, meeting notes, and project updates
• Collaborate with software and AI engineers on a proprietary platform deployed into customer cloud environments
• Contribute code and improvements to platform capabilities when needed
• Use AI tools extensively to accelerate engineering, research, analysis, and development while maintaining a strong understanding of the underlying technical decisions

📌 Required Qualifications

• 5+ years of professional, hands-on data engineering experience, ideally with significant senior-level ownership
• Advanced SQL skills
• Strong hands-on experience with at least one modern cloud data platform such as Snowflake, Databricks, BigQuery, or Redshift; experience across multiple platforms is highly valued
• Strong understanding of data architecture and data modeling principles, including common design patterns, anti-patterns, and architectural trade-offs
• Experience designing data environments across ingestion, compute, storage, transformation, and analytics/BI layers
• Hands-on cloud experience with AWS, GCP, and/or Azure beyond simply consuming cloud-hosted services
• Experience deploying or owning data platforms and working with infrastructure configuration, access controls, permissions, compute resources, and cloud architecture
• Experience making technical architecture decisions and clearly explaining the reasoning and trade-offs behind those decisions
• Excellent spoken and written English
• Strong client-facing or stakeholder-facing communication skills, with the confidence to lead technical discussions with senior stakeholders and executives
• Ability to communicate complex technical topics concisely and focus conversations on what matters
• Curiosity about AI and a strong understanding of how AI is changing modern data infrastructure, analytics, and data consumption

⭐ Desirable Experience

• Significant hands-on experience with dbt
• Experience working as a Data Engineering Consultant, Data Consultant, Data Architect, Solutions Architect, or similar client-facing technical role
• Experience working in startups, consultancies, or other lean environments requiring broad technical ownership
• Experience owning or managing a complete data or analytics platform
• Experience across two or more of Snowflake, Databricks, BigQuery, and Redshift
• Strong understanding of cloud infrastructure, platform deployment, access management, and infrastructure cost considerations
• Previous software engineering experience before moving into data engineering
• Familiarity with emerging AI/data infrastructure concepts, including MCP and AI-oriented data workflows

🎁 Benefits

Salary: $90K to 100K USD annually based on experience
PTO: 15 days
Holidays: Local or US holidays

🛂 Visa & Eligibility