Senior/Staff Data Engineer

Accountabilities:

- Set the technical direction for core data platform systems, lead architecture and design decisions, and deliver reliable production infrastructure.

- Partner with data leadership to shape the platform roadmap and evaluate architectural approaches and build-versus-buy decisions.

- Build and operate ingestion services, integrations, and data pipelines that deliver accurate and timely information.

- Establish testing, logging, alerting, and observability as core practices across the data platform.

- Own workflow orchestration infrastructure, including execution, workers, deployments, upgrades, and operational reliability.

- Improve warehouse reliability, query performance, cost efficiency, permissions, governance, and overall access management.

- Partner with Analytics Engineering on warehouse architecture and foundations supporting scalable dbt models.

- Develop APIs, event-driven ingestion services, and reusable cloud components that connect data systems.

- Use infrastructure as code to create maintainable infrastructure, reusable modules, and predictable deployments.

- Establish and improve engineering standards covering version control, CI/CD, testing, documentation, and operational practices.

- Reduce technical debt and guide the evolution of tooling and platform architecture.

- Collaborate with analytics engineers, analysts, data scientists, engineering, IT, security, and business stakeholders to clarify requirements and communicate risks, tradeoffs, and timelines.

- Support data science, analytics, AI, and LLM workflows by preparing model-ready datasets and making features available to downstream systems.

- Mentor data engineers through code reviews, pairing, design feedback, and technical coaching.

Requirements:

- 7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, with a track record of setting technical direction and delivering complex data systems.

- Deep expertise with modern cloud data warehouses such as BigQuery, Databricks, or Snowflake, including data modeling, query performance, cost management, and access control.

- Strong Python and SQL skills, with hands-on experience developing reliable ingestion and ELT pipelines and maintainable data models.

- Experience operating workflow orchestration platforms such as Prefect, Airflow, or Dagster, including deployments, upgrades, workers, and operational reliability.

- Hands-on experience with cloud infrastructure and infrastructure as code, using Terraform or equivalent technologies.

- Experience building cloud applications or backend services, including APIs, ingestion services, and event-driven workflows.

- Strong production engineering practices covering testing, logging, alerting, observability, version control, and CI/CD.

- Demonstrated ability to mentor engineers through coaching, code reviews, pairing, and design feedback.

- Excellent communication and cross-functional collaboration skills, with the ability to explain technical tradeoffs and build alignment across technical and business teams.

- Experience using AI-assisted development tools such as Codex, Cursor, or Claude Code while maintaining high standards for correctness and maintainability.

- Experience with GCP, BigQuery, Segment, and dbt is a plus.

- Experience working in developer-focused, product-led, sales-led, or usage-based businesses is beneficial.

- Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products is an advantage.

- Candidates who do not meet every listed requirement are still encouraged to apply if their experience demonstrates strong potential for the role.

Benefits:

- Compensation range of $195,000–$268,000, with offers influenced by experience, transferable skills, business needs, impact, location, and market conditions.

- Equity opportunities.

- Remote work options for employees based in Canada.

- Four weeks of paid vacation.

- 14 weeks of fully paid parental leave for all parents, including support for returning to work.

- Employer-sponsored medical coverage and dental and vision coverage, with dependent coverage available according to the applicable plan.

- Flexible Spending Accounts (FSAs) and Health Savings Accounts (HSAs).

- Long-term disability and life insurance.

- 401(k) plans.

- Monthly lifestyle stipend supporting wellness, mental health, therapy, hobbies, and related needs.

- Monthly cell phone and internet subsidy.

- Home office stipend for remote employees.

- Continuous learning benefits and professional development support.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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