Full-Time Staff Data Engineer
Ecobee is hiring a remote Full-Time Staff Data Engineer. The career level for this job opening is Manager and is accepting Canada based applicants remotely. Read complete job description before applying.
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Ecobee
Job Title
Staff Data Engineer
Posted
Career Level
Full-Time
Career Level
Manager
Locations Accepted
Canada
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Job Details
How You’ll Make an Impact:
- Cross-Domain Problem Solving: Lead the design and implementation of scalable data pipelines and systems for complex problems that require detailed understanding across multiple domains (e.g., data, machine learning, IoT, cloud infrastructure). These problems will often come with high levels of ambiguity, incomplete data, and evolving requirements.
- Architectural Impact: Contribute to ecobee’s system architecture with designs that have been battle-tested, resulting in significant, long-lasting impact within a specific domain. Solutions are expected to integrate elegantly with ecobee’s broader enterprise architecture and align with company-wide standards.
- Enterprise-Wide Architecture: Start to think beyond individual components or domains, considering ecobee’s broader architectural strategy. Collaborate with principal engineers and directors to ensure designs complement the company’s vision.
- Technical Proposals: Propose technical solutions and strategies that have a significant impact on ecobee’s data ecosystem. These solutions should drive improvement in the scalability, performance, and resilience of the company’s products and services.
- Component Ownership: Take end-to-end ownership of full components within your domain of expertise, ensuring that their design, implementation, testing, deployment, and operations meet high standards. These components will likely interact with systems in other domains, requiring careful consideration of cross-team dependencies.
- System Operations & SLAs: Define and track SLAs for the components you own, ensuring they meet operational excellence standards and contribute to the system’s overall reliability.
- Maintainability & Scalability: Systematically consider maintainability in designs and implementations, with a focus on ensuring systems can scale to support ecobee’s growing data needs.
- Mentor & Lead: Actively mentor engineers across the organization, helping them achieve concrete technical and professional goals. Drive knowledge-sharing initiatives through code reviews, technical talks, and training sessions.
- Cross-Team Collaboration: Facilitate and guide technical discussions across squads, ensuring decisions are aligned with ecobee’s strategic goals. You’ll help foster an inclusive environment where all team members feel heard and respected.
- Technical Expertise Development: Participate in “bar-raiser” groups that focus on elevating engineering standards across ecobee, including leading post-mortem reviews, design sessions, and code reviews.
- Challenging Best Practices: Continuously review existing processes, best practices, and rituals across ecobee’s engineering organization. Propose and implement improvements that enhance efficiency, collaboration, and quality.
- Delivery Metrics & Quality: Educate teams on key software delivery metrics and help track progress. Ensure that the team’s testing approaches align with accepted frameworks, and work to close gaps in quality metrics.
- Documentation & Knowledge Sharing: Foster a culture of documentation and transparency within the team and across stakeholders, ensuring that key processes and decisions are well-documented and accessible.
- Forward-Thinking Design: Anticipate future data challenges, such as scalability and security concerns, and propose strategies to avoid roadblocks. You’ll look for opportunities to improve existing solutions and identify novel approaches that haven’t been tried before.
- Technology Evaluation: Stay ahead of industry trends by evaluating and recommending new technologies that align with ecobee’s goals in data engineering, machine learning, and IoT.
- Domain-Wide Impact: Your work will have a measurable impact across multiple teams within the Data Engineering & Machine Learning Services group. This impact will often have significant customer implications, driving improvements in performance, scalability, and product capabilities.
- Economic Thinking & Risk Management: Drive a culture of thoughtful decision-making, balancing technical innovation with practical constraints like time, cost, and risk. Work closely with partner teams to prioritize capabilities that will deliver the highest business impact.
- Proactive Issue Resolution: Anticipate blockers and delays in projects before they require escalation. Proactively work to resolve these challenges by engaging with stakeholders and partner teams.
What You’ll Bring to the Table:
- 10+ years of experience in data/software engineering, with a proven track record of owning and delivering complex, cross-domain projects at scale.
- Extensive experience in building and maintaining scalable data pipelines and architecture using tools like Apache Spark, Kafka, and Airflow.
- Expertise in cloud data platforms (AWS, GCP, or Azure), with a strong focus on distributed systems, cloud managed open source frameworks and services, and IoT data integration.
- Solid understanding of end-to-end data systems, from ingestion to machine learning model deployment and inference.
- Expertise in data security, data governance, and compliance regulations relevant to the industry.
- Extensive experience in data architecture, database design and data engineering methodologies across multiple industries, with at least 5 years in a technical leadership role.
- Ability to solve problems that span multiple domains, including data engineering, machine learning, IoT, and cloud infrastructure. A deep understanding of how these domains interact is essential.
- Experience with real-time data processing, analytics platforms, and machine learning integration is highly valued.
- Proven ability to mentor and guide engineers, from juniors to senior engineers, across multiple teams. Experience facilitating technical discussions and driving consensus.
- Demonstrated ability to lead cross-functional initiatives and work effectively across squads.
- A strategic mindset, with the ability to think ahead about potential roadblocks and design systems that can scale and evolve with ecobee’s needs.
- Experience driving large technical initiatives from ideation through implementation, with a focus on creating systems that deliver high business impact.
- Demonstrated track record of contributing to new processes and practices within engineering teams. You’re comfortable challenging the status quo and driving improvements.
- Experience with software delivery metrics and ensuring that teams follow best practices in testing, code quality, and maintainability.
FAQs
What is the last date for applying to the job?
The deadline to apply for Full-Time Staff Data Engineer at Ecobee is
11th of December 2024
. We consider jobs older than one month to have expired.
Which countries are accepted for this remote job?
This job accepts [
Canada
] applicants. .
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