You are a senior cloud/DevOps engineer who thrives in a structured, client-facing environment and takes pride in building reliable, automated, and well-governed platform infrastructure. You are comfortable operating across AWS and Azure, writing infrastructure-as-code, and driving CI/CD-enabled delivery at scale. You may not have deep data warehouse or Snowflake experience today — that is expected, and we will invest in building it — but you bring the platform engineering fundamentals that underpin everything we do for our clients. You are comfortable in distributed, global teams and take full ownership of your engagements
Preferred qualifications help candidates stand out but are not required for success in this role
Experience providing operational or engineering support for a cloud-native data warehouse such as Snowflake, Amazon Redshift, or Azure Synapse — including configuration, administration, or performance tuning
Snowflake SnowPro Core certification or equivalent cloud/data platform certifications (AWS Solutions Architect, Azure Administrator, etc.)
Experience with data integration and streaming technologies such as Spark, Kafka, Fivetran, Matillion, HVR, NiFi, AWS Database Migration Service, or Azure Data Factory
Experience monitoring and supporting ETL/ELT data pipelines and scheduled data jobs in a production environment
Familiarity with workflow orchestration tools such as Apache Airflow or AWS Managed Airflow
Experience with RDBMS platforms such as Oracle or Microsoft SQL Server in an operational or engineering context
Experience with database deployment and schema migration frameworks such as Flyway or Liquibase
Familiarity with ITIL processes and working in SLA-driven support environments
Prior experience working in a managed services or Elastic Operations environment supporting multiple clients
Location & Time Zone Expectations
This role is based in LATAM and operates primarily supports clients in Eastern and Central time zones in the US
We are a remote-first company, and you should be comfortable working with a distributed global team
Some flexibility may be required to collaborate across time zones with colleagues and clients
Client needs may occasionally require flexibility in working hours to support key milestones or workshops
Strong cloud platform experience across AWS and/or Azure, including core infrastructure services (e.g., S3, ADLS, IAM, networking, compute, secrets management)
Proven hands-on experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation) — including authoring, extending, and maintaining IaC in team environments
Solid experience designing and operating CI/CD pipelines and tooling (e.g., GitHub Actions, Bitbucket Pipelines, Azure DevOps) for platform and application deployments
Proficiency in Python for scripting, automation, and operational tooling in cloud-native environments
Working knowledge of SQL — ability to read, write, and debug queries to support platform troubleshooting and data flow validation
Working knowledge of Unix/Linux environments and common system administration and scripting concepts
Strong troubleshooting, performance tuning, and root-cause analysis skills across cloud infrastructure and platform services
Active daily use of AI coding tools (Cursor, GitHub Copilot, Claude, ChatGPT, or equivalent) with demonstrated judgment about when to trust, verify, and correct AI-generated output
Ability to describe specific engineering tasks completed with AI assistance
Experience delivering projects for external or internal clients in a professional services, consulting, or managed services environment
Ability to break down complex, ambiguous platform challenges into structured, actionable steps and drive them through to completion
Strong written and verbal communication skills in English, with the ability to clearly explain technical issues and solutions to non-technical stakeholders