Data Engineer III

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. Build and own end-to-end data pipelines across Fivetran, Airflow, dbt, and Databricks .

Posted 11/2/2026full-timeRemote • CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining end-to-end data pipelines using tools like Fivetran, Airflow, and dbt, while ensuring compliance with data governance practices. Proficient in SQL and Python for production-grade coding and debugging, with strong communication skills to collaborate with cross-functional stakeholders.

Highest-signal resume keywords

Data Pipeline DevelopmentSQL ProficiencyPython ProgrammingDbt Model ManagementCloud Data Warehouse Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonDbtFivetranAirflowDatabricksSparkTerraformCI/CDData Governance

Soft Skills

Strong CommunicationAutonomous WorkStakeholder Collaboration

Tools & Technologies

AWSGCPSnowflakeBigQueryS3Lambda

Industry Keywords

ETLData QualityIncident ResponsePII HandlingAccess Controls

Tech Stack

Tools & technologies

AirflowAWSBigQueryCloudETLGoogle Cloud PlatformPythonSnowflakeSparkSQLTerraform

About the role

Key responsibilities & impact

Build and own end-to-end data pipelines across Fivetran, Airflow, dbt, and Databricks
Design and maintain tested, documented, reusable dbt models for the semantic layer
Partner with Marketing, Finance, Sales, Legal, HR, and Product stakeholders to scope requirements and define pipeline specifications
Contribute to Terraform-managed Fivetran, GCP, and AWS infrastructure
Follow and contribute to engineering standards for testing, CI/CD, code review, observability, and documentation
Resolve complex ETL and data quality issues
Monitor pipelines for SLA compliance and participate in incident response
Apply data governance practices for PII and compliance requirements
Explain technical concepts and feasibility to non-technical stakeholders

Requirements

What you’ll need

4+ years of professional experience as a Data Engineer, with demonstrated ownership of production pipelines
Strong SQL and Python; comfortable writing production-grade code, debugging complex pipelines, and optimizing queries
Hands-on experience with a cloud data warehouse (Snowflake strongly preferred; BigQuery or equivalent acceptable)
Solid dbt experience — has built and maintained models in a production dbt project
Experience with orchestration tools — Airflow and Fivetran required; Dagster or equivalent a plus
Experience with Databricks and Spark for custom modeling and transformation workloads
Experience with AWS (Airflow, S3, Lambda) and GCP (BigQuery and adjacent services)
Ability to work autonomously and scope ambiguous asks with stakeholders
Strong communication skills for explaining technical tradeoffs to non-technical partners
Familiarity with PII handling and access controls
Experience with CI/CD for data pipelines
Experience contributing to a team dbt project
Familiarity with Terraform or another IaC tool