Data Engineer at SPECTRAFORCE

Ontario, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

29 Dec, 26

Salary

45000.0

Posted On

30 Sep, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Industry

Consumer Services

Description

Key ResponsibilitiesBuild and own end-to-end data pipelines across Fivetran, Airflow, dbt, and Databricks, selecting the right tool for each problem with guidance from senior engineering leadership when needed.
Design, maintain, test, document, and optimize dbt models that support the team’s semantic layer.
Partner with stakeholders across Marketing, Finance, Sales, Legal, HR, and Product to scope data requirements and translate them into pipeline specifications.
Contribute to Terraform-managed infrastructure for Fivetran connectors, GCP resources, and AWS components.
Follow and contribute to engineering standards for testing, CI/CD, code reviews, observability, and documentation.
Independently resolve complex ETL and data quality issues, escalating only when architectural tradeoffs are involved.
Monitor data pipelines for SLA compliance and participate in incident response as needed.
Apply data governance practices to ensure proper handling of PII and compliance with business-unit-specific requirements.
Communicate technical concepts clearly to non-technical stakeholders and advise on feasibility, tradeoffs, and implementation options.
Required Qualifications4+ years of professional experience as a Data Engineer, with demonstrated ownership of production data pipelines. Candidates with 3+ years of strong, relevant experience may also be considered.
Hands-on experience contributing to a production dbt project.
Experience with CI/CD practices for data pipelines.
Familiarity with Terraform or another infrastructure-as-code tool.
Strong SQL and Python skills, including the ability to write production-grade code, debug complex pipelines, and optimize queries.
Hands-on experience with a cloud data warehouse; Snowflake is strongly preferred, while BigQuery or equivalent platforms are acceptable.
Experience with orchestration and ingestion tools, including Airflow and Fivetran.
Experience with Databricks and Spark for custom modeling and transformation workloads.
Experience working with AWS services such as S3, Lambda, and Airflow, as well as GCP services such as BigQuery.
Ability to work autonomously, scope ambiguous requests with stakeholders, and deliver solutions with minimal oversight.
Strong communication skills, including the ability to explain technical tradeoffs to non-technical audiences.
Security-first mindset with familiarity in PII handling, access controls, and data governance practices.

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Responsibilities

Key ResponsibilitiesBuild and own end-to-end data pipelines across Fivetran, Airflow, dbt, and Databricks, selecting the right tool for each problem with guidance from senior engineering leadership when needed.
Design, maintain, test, document, and optimize dbt models that support the team’s semantic layer.
Partner with stakeholders across Marketing, Finance, Sales, Legal, HR, and Product to scope data requirements and translate them into pipeline specifications.
Contribute to Terraform-managed infrastructure for Fivetran connectors, GCP resources, and AWS components.
Follow and contribute to engineering standards for testing, CI/CD, code reviews, observability, and documentation.
Independently resolve complex ETL and data quality issues, escalating only when architectural tradeoffs are involved.
Monitor data pipelines for SLA compliance and participate in incident response as needed.
Apply data governance practices to ensure proper handling of PII and compliance with business-unit-specific requirements.
Communicate technical concepts clearly to non-technical stakeholders and advise on feasibility, tradeoffs, and implementation options.
Required Qualifications4+ years of professional experience as a Data Engineer, with demonstrated ownership of production data pipelines. Candidates with 3+ years of strong, relevant experience may also be considered.
Hands-on experience contributing to a production dbt project.
Experience with CI/CD practices for data pipelines.
Familiarity with Terraform or another infrastructure-as-code tool.
Strong SQL and Python skills, including the ability to write production-grade code, debug complex pipelines, and optimize queries.
Hands-on experience with a cloud data warehouse; Snowflake is strongly preferred, while BigQuery or equivalent platforms are acceptable.
Experience with orchestration and ingestion tools, including Airflow and Fivetran.
Experience with Databricks and Spark for custom modeling and transformation workloads.
Experience working with AWS services such as S3, Lambda, and Airflow, as well as GCP services such as BigQuery.
Ability to work autonomously, scope ambiguous requests with stakeholders, and deliver solutions with minimal oversight.
Strong communication skills, including the ability to explain technical tradeoffs to non-technical audiences.
Security-first mindset with familiarity in PII handling, access controls, and data governance practices.