Senior Data, Platform & Solutions Engineer

Sur Global; Argentina; On-site; ARS 136,310,000 - 151,455,000; Full time

Benefits offered by this job

Salary: USD 90K–100K per year

PTO: 15 days

Holidays: Local or US holidays

Job summary

Sur Global is seeking a highly experienced Senior Data Engineer who combines deep data engineering with data architecture, cloud ownership, and direct client engagement. You will own multiple client projects, lead architecture discussions, and deliver end-to-end data solutions across cloud platforms.

The role requires hands-on experience with platforms like Snowflake, Databricks, BigQuery, or Redshift, and strong English communication skills to interact with executives and stakeholders.

Qualifications

• 5+ years of hands-on data engineering experience with senior ownership.
• Advanced SQL skills.
• Experience with Snowflake, Databricks, BigQuery, or Redshift across multiple platforms.
• Strong data architecture and modeling knowledge.
• Hands-on cloud experience with AWS, GCP, and/or Azure beyond services.
• Experience deploying data platforms and managing access/compute resources.
• Excellent spoken and written English.
• Strong client-facing communication and ability to lead discussions with executives.
• Curiosity about AI and its impact on data infrastructure.

Responsibilities

• Own the technical delivery of data projects from client conversations through architecture, implementation, and ongoing delivery.
• Lead client discussions to understand business requirements and translate them into technical solutions.
• Design modern data architectures spanning ingestion, transformation, compute, storage, analytics, and BI layers.
• Make informed architecture recommendations based on trade-offs, cost, scalability, and maintainability.
• Build and maintain production data pipelines, transformations, models, and platform components.
• Work hands-on with Snowflake, Databricks, BigQuery, and/or Redshift.
• Build and maintain transformation workflows using SQL and dbt.
• Work within AWS, GCP, and/or Azure environments including deployment and access controls.
• Take end-to-end ownership to deliver projects without relying on separate teams.
• Manage multiple client projects with priorities, timelines, and thorough documentation.
• Produce client-facing documentation, presentations, and project updates.
• Collaborate with software and AI engineers on a proprietary platform deployed in customer cloud environments.
• Contribute code and improvements to platform capabilities as needed.
• Leverage AI tools to accelerate engineering while understanding underlying decisions.

Skills

Advanced SQL

Data architecture

Cloud data platforms

AWS/GCP/Azure

Client-facing communication

English proficiency

AI concepts familiarity

Tools

dbt

Job description

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.

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.

We are especially interested in engineers who have worked in consulting, startups, or other environments where they have had broad ownership rather than operating within one narrow function of a large data organization.

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

Requirements

• 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

Preferred

• 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