Staff Data Engineer

This is a fully remote position, open to applicants in Canada, +1 more country.

📋 Description

• Take full ownership of data initiatives from the technical design phase through implementation, validation, production rollout, and ongoing operation.

• Design and sustain scalable data ingestion and transformation pipelines across application databases, APIs, third-party integrations, and healthcare data sources.

• Link data architecture, models, and integrations to workflows for customers, operators, and internal teams.

• Develop reusable data models and shared definitions that support product features, reporting, analytics, and machine learning.

• Integrate validation, monitoring, alerting, and recovery mechanisms into data pipelines.

• Enhance processing efficiency, query performance, and infrastructure costs while managing increasing data volume and product complexity.

• Collaborate with product, operations, platform, machine learning, and engineering teams to convert business requirements into effective data solutions.

• Participate in technical design, conduct code reviews, create documentation, offer mentorship, and uphold maintainable data engineering practices.

⛳️ Requirements

• Over 7 years of engineering experience with a focus on data engineering, data platforms, or backend systems that involve significant data processing.

• Strong expertise in SQL and TypeScript.

• Proven experience in designing ETL/ELT pipelines, data models, and orchestration workflows.

• Understanding of dependencies, retries, backfills, and schema evolution.

• Solid foundation in relational databases, data warehouses, and cloud infrastructure.

• Experience with query optimization and scalable storage and processing solutions.

• Capability to manage production data systems comprehensively, from design to rollout and ongoing support.

• Good judgment regarding product and workflow considerations.

• Practical mindset towards data quality, observability, access controls, and the management of sensitive information.

• Ability to independently scope, plan, and execute complex, open-ended challenges.

• Effective communication skills with both technical and nontechnical stakeholders.

• Familiarity with healthcare data, EHR integrations, or interoperability standards such as FHIR is a plus.

• Experience in supporting machine learning pipelines, AI products, or datasets that are utilized for model training and evaluation is a plus.

• Knowledge of Databricks, dbt, Airflow, Dagster, Spark, or similar frameworks is advantageous.

• Previous experience building data infrastructure in a rapidly growing startup is a plus.

🏝️ Benefits

• Option for remote work in Toronto and Vancouver.

• Hybrid work option available in New York.