Senior Data, Platform & Solutions Engineer
New
S
SurData engineering
Brazil. Argentina. Colombia. Costa Rica. Mexico. ChileFull-TimeSenior
Salary100,000 USD per year
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Job Details
- Languages
- Excellent spoken and written English
- Experience
- 5+ years of professional, hands-on data engineering experience
- Required Skills
- AWSSQLGCPMicrosoft AzureSnowflakeData engineeringBigQuerydbtDatabricks
Requirements
- Have 5+ years of professional, hands-on data engineering experience, ideally with significant senior-level ownership.
- Demonstrate advanced SQL skills.
- Have hands-on experience with at least one modern cloud data platform, such as Snowflake, Databricks, BigQuery, or Redshift.
- Understand data architecture and modeling principles, including design patterns, anti-patterns, and architectural trade-offs.
- Have experience designing data environments across ingestion, compute, storage, transformation, and analytics/BI layers.
- Have hands-on experience with AWS, GCP, and/or Azure beyond consuming cloud-hosted services.
- Have experience deploying or owning data platforms, including infrastructure configuration, access controls, permissions, compute resources, and cloud architecture.
- Be able to make technical architecture decisions and explain the reasoning and trade-offs.
- Have excellent spoken and written English and strong client- or stakeholder-facing communication skills.
- Be able to lead technical discussions with senior stakeholders and executives and explain complex technical topics concisely.
- Be curious about AI and understand how it is changing data infrastructure, analytics, and data consumption.
- Preferred: significant hands-on dbt experience; experience in a client-facing technical role, lean environment, or owning a complete data or analytics platform; experience across multiple listed data platforms; cloud infrastructure and cost knowledge; prior software engineering experience; or familiarity with MCP and AI-oriented data workflows.
Responsibilities
- Own technical delivery of data projects from initial client conversations through architecture, implementation, and ongoing delivery.
- Lead client discussions, clarify business and technical requirements, and translate ambiguous problems into technical solutions.
- Design data architectures across ingestion, transformation, compute, storage, analytics, and BI.
- Recommend architectures based on technical trade-offs, cost, scalability, maintainability, and client requirements.
- Build and maintain production data pipelines, transformations, models, and platform components.
- Work with modern data platforms such as Snowflake, Databricks, BigQuery, and Redshift, and build transformation workflows using SQL and tools such as dbt.
- Work in AWS, GCP, and/or Azure environments, including platform deployment, infrastructure configuration, access controls, permissions, and cloud resources.
- Manage multiple client projects, maintaining priorities, timelines, documentation, and follow-up.
- Produce client-facing documentation, presentations, meeting notes, and project updates.
- Collaborate with software and AI engineers, contribute platform code and improvements, and use AI tools to support engineering, research, analysis, and development.
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