Solutions Engineer, Healthcare

Grupo Protege

Solutions Engineer managing cross-cloud movements of large healthcare datasets at Protege. Focused on execution, reliability, and safe data movement, enhancing healthcare data delivery.

Posted 4/27/2026full-timeRemote • 🇧🇷 BrazilMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AirflowAssemblyAWSAzureCloudLinuxMacOSPythonSQL

About the role

Key responsibilities & impact

Own cross-cloud data movement and delivery
Execute and monitor large-scale data transfers across AWS S3, Google Cloud Storage, Azure Blob, Snowflake, and customer environments.
Use CLI tools such as rclone, s5cmd, and cloud-native utilities to move data safely and efficiently.
Manage credentials, permissions, manifests, and delivery packaging artifacts required for ingestion, subset delivery, and handoff workflows.
Build structured data assembly and lightweight transformation workflows
Use Python and SQL to join datasets, add derived columns, clean data, and validate CSV, Parquet, and database tables.
Support customer-specific assembly work that turns raw inputs into delivery-ready datasets.
Apply a high bar for data integrity, structure, and reproducibility before handoff.
Operate internal pipelines with production discipline
Leverage Protege's Dagster-based platform to orchestrate data processing and delivery.
Maintain clean separation between pre-production and production workflows and validate configs before runs.
Build lightweight scripts and command-line workflows for filtering, manifest generation, validation, and recovery.
Create leverage for the team and platform
Document steps, outputs, and recovery paths for auditability and repeatability.
Identify recurring delivery patterns, failure modes, and manual toil.
Partner with Engineering to turn one-off operational work into repeatable platform capabilities and test new tooling before go-live.

Requirements

What you’ll need

Strong hands-on experience with data pipelines, both orchestrated and manual, in real production environments.
Fluency with command-line tooling in Linux or MacOS and strong scripting ability in Python, SQL, and Bash/shell.
Experience working with cloud storage systems and large-scale cross-cloud data movement.
High bar for data integrity, validation, reproducibility, and auditability - especially for regulated data.
Calm, methodical debugging instincts and strong operational judgment about when to rerun, recover, or escalate.
Ability to manage multiple delivery workflows simultaneously while collaborating well with a distributed team.
Bonus if you have experience with AWS S3, GCS, Azure Blob, Snowflake, IAM debugging, Dagster/Airflow, healthcare data, or AI training data.

Benefits

Comp & perks

Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data pipelinesPythonSQLBashdata integritydata validationdata reproducibilitydata transformationcommand-line scriptinglarge-scale data movement

Soft Skills

operational judgmentdebuggingcollaborationmethodical approachmulti-tasking