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Senior Staff Data Ops Engineer (Canada)

At PeakMetrics, we stand at the forefront of narrative intelligence, harnessing the power of advanced machine learning to safeguard enterprises and government agencies from social media manipulation and narrative attacks. Our platform rapidly sifts through millions of unstructured, cross-channel media datasets, transforming them into actionable insights. By identifying adversarial online messaging, understanding its audience, and providing crucial context such as source credibility, we empower our customers to effectively respond to digital threats.

Our team tackled some of today's most intricate media challenges, from crisis management to thwarting state-sponsored disinformation campaigns. Our goal is unwavering: to shield our clients from the risks of social media manipulation and emerging narrative threats by detecting and remediating from harmful online trends.

We are looking for an experienced and visionary Senior Data Engineer and DevOps to lead the design, execution, and evolution of our data infrastructure and DevOps strategies. In this role, you will create and collaborate with the Data/Product/Engineering teams to implement a cohesive vision for scalable, secure, and efficient systems, while building a high-performing team of data engineers and DevOps professionals. You will be pivotal in ensuring the seamless integration of data systems with business needs and driving innovation across the organization.

What you will accomplish: 

  • Develop and execute the long-term vision for the organization’s data engineering and DevOps strategies.

  • Collaborate with senior leadership to prioritize initiatives, set objectives, and define measurable outcomes.

  • Stay ahead of industry trends, tools, and technologies to ensure competitive advantage and efficiency.

  • Build, mentor, and lead a diverse team of data engineers and DevOps professionals.

  • Foster a culture of innovation, accountability, and collaboration within the team.

  • Establish best practices for performance management, career development, and skills growth.

  • Oversee the design, development, and maintenance of scalable data pipelines, warehouses, and processing frameworks.

  • Build the infrastructure and codebase required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies.

  • Drive the implementation of best practices in data governance, quality, and security.

  • Ensure the availability, reliability, and performance of data systems 

  • Lead the adoption of modern DevOps methodologies to streamline CI/CD pipelines and deployment processes.

  • Ensure robust monitoring, logging, and alerting systems are in place for all applications and data infrastructure.

  • Partner with cross-functional teams, including product, analytics, and engineering, to understand and deliver on business needs.

  • Present project updates, performance metrics, and strategic initiatives to leadership.

Would love to hear from you if you have:

  • 13+ years of experience in engineering, with at least 5+ years in data engineering, data ops, or related roles.

  • Proven experience in designing and implementing data architectures, ETL processes, and DevOps pipelines.

  • Expertise in cloud platforms (AWS, Azure, or GCP) and cloud-native solutions.

  • Strong understanding of data governance, security, and compliance standards (e.g., GDPR, HIPAA).

  • Proficiency in programming and scripting languages (e.g., Python, Java, Bash).

  • Experience with modern DevOps tools such as Kubernetes, Docker, Terraform, Jenkins, or similar.

  • Track record of successfully managing and scaling high-performing technical teams.

  • Experience with big data technologies (e.g., Kafka).

  • Familiarity with ML/AI infrastructure and frameworks.

  • Hands-on experience with both relational and non-relational databases (e.g., SQL, NoSQL).

  • Certifications in cloud platforms or DevOps practices are a plus.

  • You have maintained data management systems and have built new data pipelines from scratch.

  • You are comfortable automating data flows with resilient code using Python.

  • Experience with Dagster or other data orchestration platforms such as Airflow.

  • You have strong database architecture design and management knowledge in both structured and unstructured data. 

  • Advanced knowledge of Elasticsearch or OpenSearch, including configuration, operation, and using for search

  • Extensive experience working with SQL, SQLAlchemy with Postgres, Athena, Parquet and Iceberg. 

  • You are able to define and communicate data architecture requirements, keeping current with data management best practices.

  • Your clarity of thought is always apparent in your crisp and articulate emails, Slack chats, phone calls, and in-person conversations. You ask questions to better understand the context around your work and what you need to do to be successful.

  • Exceptional leadership, communication, and decision-making abilities.

  • Strong analytical mindset with a solution-oriented approach.

  • Ability to balance strategic vision with tactical execution.

  • We are 100% remote and distributed across multiple time zones, and we use remote collaboration tools (e.g. Slack, Notion, GSuite, Zoom) to stay connected and productive.

Benefits

  • Remote-first culture

  • Health insurance, 401(k) and other benefits

  • Flexible work schedule and unlimited time off

  • Opportunities for professional growth and development

  • A vibrant and inclusive company culture

PeakMetrics is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, or disability status.

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Average salary estimate

$140000 / YEARLY (est.)
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$120000K
$160000K

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What You Should Know About Senior Staff Data Ops Engineer (Canada), PeakMetrics

At PeakMetrics, we are redefining the landscape of narrative intelligence with our cutting-edge approach to machine learning, and we’re on the lookout for a Senior Staff Data Ops Engineer to join our dynamic team. This isn’t just any job; it’s a chance to make a significant impact by safeguarding enterprises and government agencies from the waves of social media manipulation and narrative attacks that threaten their integrity. In this role, you’ll work hand-in-hand with our Data, Product, and Engineering teams to craft a robust vision for our data infrastructure and DevOps strategies. Your leadership will guide the design and execution of scalable systems that align perfectly with our business needs. Imagine mentoring and building a diverse team of specialists who will play a pivotal role in addressing complex media challenges, from crisis management to counteracting disinformation. You'll stay ahead of industry trends, ensure the security of our data governance, and implement best practices for optimal data processing. This role allows you not only to drive innovation within PeakMetrics but also to foster a culture of collaboration and accountability. Your experience will shine as you lead the charge in data integration, modern DevOps methodologies, as well as establish and maintain the reliability of data systems. If you're passionate about tackling intricate media challenges while leading a high-performing team, then this position at PeakMetrics awaits your unique expertise!

Frequently Asked Questions (FAQs) for Senior Staff Data Ops Engineer (Canada) Role at PeakMetrics
What are the responsibilities of a Senior Staff Data Ops Engineer at PeakMetrics?

As a Senior Staff Data Ops Engineer at PeakMetrics, you will develop and execute a long-term vision for data engineering and DevOps strategies. Your duties will include overseeing the design and maintenance of scalable data pipelines and infrastructures, collaborating with leadership to set objectives, and ensuring data security and governance compliance.

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What qualifications do I need to become a Senior Staff Data Ops Engineer at PeakMetrics?

To qualify for the Senior Staff Data Ops Engineer position at PeakMetrics, you should have over 13 years of engineering experience, including at least 5 years focused on data engineering or related fields. Proven expertise in cloud platforms like AWS and experience with tools such as Kubernetes and Terraform are also essential.

Join Rise to see the full answer
How does PeakMetrics support the growth of its Senior Staff Data Ops Engineers?

At PeakMetrics, we are committed to your professional development. We provide opportunities for career advancement, a flexible work schedule, and access to resources that encourage skill growth. Our mentoring culture ensures that you receive the support needed to thrive in your role.

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What is the work culture like for a Senior Staff Data Ops Engineer at PeakMetrics?

PeakMetrics boasts a vibrant, remote-first culture that embraces inclusivity and collaboration. As a Senior Staff Data Ops Engineer, you'll engage with a distributed team across multiple time zones, utilizing remote collaboration tools to stay connected, productive, and engaged with your peers.

Join Rise to see the full answer
What are the key technologies a Senior Staff Data Ops Engineer at PeakMetrics should be familiar with?

A Senior Staff Data Ops Engineer at PeakMetrics should be proficient in SQL and various cloud platforms like AWS. Familiarity with big data technologies, modern DevOps tools such as Docker and Jenkins, and experience in data orchestration platforms like Dagster or Airflow will be vital for success in this role.

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Common Interview Questions for Senior Staff Data Ops Engineer (Canada)
Can you describe your experience with data architecture design as a Senior Staff Data Ops Engineer?

When discussing your experience, focus on specific projects where you designed data architectures. Highlight how you approached the design process, the technologies used, and the impact your architecture had on the organization’s data strategy.

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What strategies do you use to ensure data security and governance in your projects?

Discuss the frameworks and standards you follow for data security, such as GDPR or HIPAA. Provide examples of how you implemented these strategies in previous roles, ensuring data integrity and compliance with regulation.

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How do you prioritize initiatives as a Senior Staff Data Ops Engineer?

Explain your method of collaborating with senior leadership to discuss business needs and technical requirements. Use examples of past projects to illustrate how you set objectives and achievable measurable outcomes based on these discussions.

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What modern DevOps tools have you implemented in your previous roles?

Share the specific tools you've used, such as Kubernetes or Jenkins. Describe how you implemented them to enhance CI/CD pipelines, detailing the challenges faced and the overall benefits achieved for the team.

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How do you mentor and develop junior engineers on your team?

Discuss your mentorship style, including one-on-one sessions, knowledge-sharing practices, and opportunities you provide for skill growth. Be sure to highlight any successful mentorship experiences you've had that demonstrate your leadership abilities.

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Can you explain your experience with ETL processes?

Provide details on the ETL processes you've designed and implemented, including the tools you used and any improvements made to efficiency or accuracy. Share a specific project to illustrate your hands-on experience.

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What is your approach when integrating data systems with business needs?

Talk about your experience in collaborating with cross-functional teams to understand requirements and translate them into technical specifications. Use examples to show how you've successfully aligned data analytics with business objectives.

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How do you keep up with industry trends and technological advancements?

Share how you incorporate continuous learning into your professional routine, such as attending webinars, participating in forums, or obtaining certifications. Highlight a recent trend that you adopted and its impact on your work.

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What metrics do you use to measure the performance of data systems?

Discuss the specific KPIs and metrics you monitor to ensure performance and reliability, such as uptime, response time, and data quality indicators. Use examples from past projects to illustrate your approach.

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How do you handle conflicting priorities in a remote team environment?

Provide examples of how you employ effective communication tools and strategies to resolve conflicts and manage multiple priorities. Highlight your ability to maintain team collaboration remotely and ensure project timelines are met.

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DATE POSTED
March 28, 2025

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