Senior Data, Platform & Solutions Engineer

This is a fully remote position, open to applicants in Brazil, +5 more countries.

📋 Description

• Take charge of the technical delivery of data initiatives from the initial client discussions to architecture, implementation, and continuous delivery.

• Facilitate client conversations to grasp business and technical requirements, converting ambiguous challenges into actionable technical solutions.

• Design contemporary data architectures that encompass ingestion, transformation, compute, storage, analytics, and BI layers.

• Provide architectural recommendations based on technical trade-offs, cost considerations, scalability, maintainability, and client specifications.

• Construct and oversee production data pipelines, transformations, models, and platform components.

• Engage directly with Snowflake, Databricks, BigQuery, and/or Redshift.

• Develop and manage SQL and dbt transformation workflows.

• Operate within AWS, GCP, and/or Azure environments, including deployment, infrastructure configuration, access, permissions, and cloud resources.

• Assume complete ownership of delivery processes.

• Manage several client projects with defined priorities, timelines, documentation, and follow-up actions.

• Create client-oriented documentation, presentations, meeting summaries, and project updates.

• Collaborate with software and AI engineers on a proprietary platform utilized in customer cloud settings.

• Contribute to code and platform enhancements.

• Leverage AI tools to expedite engineering, research, analysis, and development while being mindful of the foundational technical decisions.

⛳️ Requirements

• Over 5 years of professional, hands-on experience in data engineering.

• Proficient in advanced SQL.

• Strong practical experience with at least one modern cloud data platform such as Snowflake, Databricks, BigQuery, or Redshift.

• In-depth understanding of data architecture and data modeling principles, including design patterns, anti-patterns, and architectural trade-offs.

• Experience in designing data environments across ingestion, compute, storage, transformation, and analytics/BI layers.

• Hands-on cloud experience with AWS, GCP, and/or Azure beyond merely utilizing cloud-hosted services.

• Experience in deploying or managing data platforms and working with infrastructure configuration, access controls, permissions, compute resources, and cloud architecture.

• Proven capability in making technical architecture decisions and articulating the rationale and trade-offs.

• Excellent proficiency in spoken and written English.

• Strong communication skills with clients or stakeholders, including leading technical discussions with senior stakeholders and executives.

• Ability to convey complex technical topics succinctly.

• Interest in AI and comprehension of its influence on modern data infrastructure, analytics, and data consumption.

• Significant hands-on experience with dbt is preferred.

• Experience in client-facing technical roles such as Data Engineering Consultant, Data Consultant, Data Architect, Solutions Architect, or similar is preferred.

• Background in startup, consultancy, or lean environments is preferred.

• Experience in owning or managing a complete data or analytics platform is preferred.

• Familiarity with two or more of Snowflake, Databricks, BigQuery, and Redshift is preferred.

• Strong understanding of cloud infrastructure, platform deployment, access management, and infrastructure cost considerations is preferred.

• Previous experience in software engineering is preferred.

• Knowledge of MCP and AI-oriented data workflows is preferred.

🏝️ Benefits

• 15 days of paid time off (PTO).

• Observance of local or US holidays.