Staff Data Engineer

ExaCare AI

. Own data initiatives end-to-end, from technical design through implementation, validation, production rollout, and ongoing operation .

Posted 10/10/2026full-timeRemote • Canada, United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, including end-to-end ownership of data initiatives, designing scalable ETL/ELT pipelines, and optimizing data processing and storage. Proficient in SQL and TypeScript, with a strong understanding of relational databases and cloud infrastructure.

Highest-signal resume keywords

Data Engineering ExperienceSQL ProficiencyETL/ELT Pipeline DesignData Model DevelopmentHealthcare Data Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLTypeScriptETL/ELT Pipeline DesignData Model DevelopmentQuery OptimizationRelational DatabasesData WarehousingCloud InfrastructureData Quality ManagementData Processing

Soft Skills

Clear CommunicationGood Product JudgmentIndependent Execution

Tools & Technologies

DatabricksDbtAirflowDagsterSpark

Industry Keywords

Healthcare DataEHR IntegrationsInteroperability StandardsMachine Learning PipelinesData Infrastructure

Tech Stack

Tools & technologies

AirflowCloudETLSparkSQLTypeScript

About the role

Key responsibilities & impact

Own data initiatives end-to-end, from technical design through implementation, validation, production rollout, and ongoing operation
Design and maintain scalable ingestion and transformation pipelines across application databases, APIs, third-party integrations, and healthcare data sources
Connect data architecture, models, and integrations to customer, operator, and internal team workflows
Create reusable data models and shared definitions supporting product features, reporting, analytics, and machine learning
Build validation, monitoring, alerting, and recovery into pipelines
Improve processing efficiency, query performance, and infrastructure costs as data volume and product complexity grow
Partner with product, operations, platform, ML, and engineering teams to translate business needs into data solutions
Contribute to technical design, code reviews, documentation, mentorship, and maintainable data engineering practices

Requirements

What you’ll need

7+ years of engineering experience focused on data engineering, data platforms, or backend systems involving substantial data processing
Strong proficiency with SQL and TypeScript
Experience designing ETL/ELT pipelines, data models, and orchestration workflows
Understanding of dependencies, retries, backfills, and schema evolution
Strong fundamentals in relational databases, data warehouses, and cloud infrastructure
Experience with query optimization and scalable storage and processing
Ability to own production data systems end-to-end, from design through rollout and ongoing support
Good product and workflow judgment
Practical approach to data quality, observability, access controls, and handling sensitive information
Ability to scope, plan, and execute independently on complex, open-ended problems
Clear communication with technical and nontechnical partners
Experience with healthcare data, EHR integrations, or interoperability standards such as FHIR is nice to have
Experience supporting ML pipelines, AI products, or datasets used for model training and evaluation is nice to have
Familiarity with Databricks, dbt, Airflow, Dagster, Spark, or comparable frameworks is nice to have
Experience building data infrastructure in a fast-growing startup is nice to have

Benefits

Comp & perks

Remote work option in Toronto and Vancouver
Hybrid work option in New York