6 часов назад
Staff Analytics Engineer (Data Analytics)
147 700 - 191 900CAD
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Staff Analytics Engineer (dbt/GCP): Owning and evolving the Silver and Gold layers of a lakehouse, curated analytical datasets, semantic models, and production data workflows with an accent on data modeling, quality, governance, and reliability. Focus on designing batch and real-time transformations, enforcing data contracts and SLOs, optimizing cloud costs, and providing technical leadership across analytics and engineering.
Location: Toronto, Canada; hybrid schedule with in-office work required on Wednesdays and Thursdays
Salary: 147,700–191,900 CAD annually, plus variable compensation including short-term and long-term incentives.
Company
, including its ecobee subsidiary, develops connected-home, smart thermostat, backup generator, and sustainable energy products for homes and businesses.
What you will do
- Own and evolve the Silver and Gold layers of the lakehouse using dbt.
- Publish certified, reusable datasets and maintain the semantic and metrics layer for self-service analytics.
- Design transformation workflows and collaborate with data engineering on ingestion, schemas, architecture, and end-to-end pipelines.
- Implement data quality, observability, governance, data contracts, schema change management, and SLO-driven reliability practices.
- Operate critical production data flows, including incident response, runbooks, root cause analysis, alerting, and continuous improvement.
- Drive technical standards, code reviews, documentation, stakeholder alignment, and mentorship across analytics engineering.
Requirements
- Deep hands-on experience with dbt, modular tested models, project structures at scale, and dimensional data modeling.
- Proficiency in Python and SQL, with experience optimizing warehouses and cloud compute, storage, and query costs.
- Experience with GCP services including BigQuery, Dataflow, and Cloud Storage, plus Apache Airflow or Cloud Composer.
- Experience designing batch and real-time processing solutions and familiarity with distributed processing technologies such as Spark and Kafka.
- Strong knowledge of data quality, governance, observability, data contracts, SLO-driven operations, lineage, versioning, and data-as-a-product principles.
- Experience with CI/CD, Git, GitHub, privacy and security controls, and communicating architectural trade-offs to technical and non-technical stakeholders.
Culture & Benefits
- Hybrid work with remote flexibility on days without required office attendance.
- Medical, dental, and vision coverage, life and long-term disability insurance.
- Flexible spending and health savings accounts, accrued paid time off, and paid holidays.
- RRSP retirement benefits and variable compensation opportunities.
- Background check required for the hired candidate.
Hiring process
- 30-minute phone call with Talent Acquisition.
- 75-minute video interview with the Hiring Manager covering technical, behavioral, and situational questions.
- 90-minute technical video interview with team members followed by a 45-minute final interview with the VP.
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