Analytics Engineer

• Build and maintain curated analytical datasets, data marts, semantic models, and reusable data products
• Transform enterprise data into trusted, scalable, business-ready assets
• Design analytical models balancing performance, usability, and scalability
• Create reusable business logic and data transformations
• Develop semantic models, certified metrics, KPIs, and shared business logic
• Translate complex business requirements into reliable technical solutions
• Support self-service analytics with intuitive and governed data products
• Document and maintain traceability of analytical assets
• Implement automated testing, validation, reconciliation, and data quality controls
• Lead technical design reviews and contribute to analytics engineering best practices
• Apply version control, code review, deployment automation, and continuous improvement
• Partner with Data Governance to embed ownership, lineage, controls, and traceability
• Develop analytical foundations for advanced analytics, machine learning, and AI
• Collaborate with Data Pipeline Engineering, BI, Analytics, and business teams
• Modernize enterprise analytics and move beyond one-off reporting solutions
• Serve as a trusted technical advisor and mentor colleagues
• Build partnerships that foster collaboration, knowledge-sharing, and innovation

Senior Analytics Engineer

• Develop and maintain curated analytical datasets, data marts, semantic models, and reusable data products
• Transform organizational data into reliable, scalable assets that are ready to support business needs
• Design analytical models that balance performance, usability, and sustainability
• Create reusable business logic and data transformations
• Develop semantic models, certified metrics, KPIs, and shared business logic
• Collaborate with business partners and analytics stakeholders to translate complex requirements into reliable technical solutions
• Support self-service analytics capabilities
• Ensure analytical assets are fully documented, traceable, and understandable
• Implement automated mechanisms for data testing, validation, reconciliation, and quality control
• Lead technical design reviews and contribute to analytics engineering best practices
• Apply version control, code review, deployment automation, and continuous improvement
• Collaborate with data governance teams on data ownership, traceability, controls, and lineage
• Develop analytical foundations that support advanced analytics, machine learning, and artificial intelligence
• Collaborate with data pipeline engineering, business intelligence, and analytics teams
• Modernize the organization’s analytics capabilities
• Serve as a trusted technical advisor
• Provide mentorship and guidance on analytical modeling, data transformations, and data products
• Build partnerships that foster collaboration, knowledge sharing, and innovation
• Demonstrate autonomy, accountability, and leadership in delivering high-quality solutions

• Build and maintain curated analytical datasets, data marts, semantic models, and reusable data products
• Transform enterprise data into trusted, scalable, business-ready assets
• Design analytical models balancing performance, usability, and scalability
• Create reusable business logic and data transformations
• Develop semantic models, certified metrics, KPIs, and shared business logic
• Translate complex business requirements into reliable technical solutions
• Support self-service analytics with intuitive and governed data products
• Document and ensure traceability of analytical assets
• Implement automated testing, validation, reconciliation, and data quality controls
• Lead technical design reviews and promote analytics engineering best practices
• Apply version control, code review, deployment automation, and continuous improvement
• Partner with Data Governance on ownership, lineage, controls, and traceability
• Develop foundations supporting advanced analytics, machine learning, and AI capabilities
• Collaborate with Data Pipeline Engineering, BI, Analytics, and business teams
• Modernize enterprise analytics and replace one-off reporting with reusable products
• Serve as a technical advisor and mentor teams on analytical modeling and data product development

• Lead stakeholder engagements to understand mission objectives, operational challenges, current-state workflows, and future-state needs
• Document business requirements, functional requirements, user stories, acceptance criteria, and process flows
• Analyze sustainment, logistics, maintenance, supply, and readiness processes to identify gaps, inefficiencies, risks, and improvement opportunities
• Translate mission and operational needs into system, reporting, and data requirements for technical teams
• Support prioritization, scope definition, and impact analysis for system enhancements, integrations, and process changes
• Partner with product, operations, architecture, data science, and engineering teams to define solution options and recommend approaches
• Map current-state and future-state processes, handoffs, and system interactions across sustainment workflows
• Support the design of integrations, workflow automation, and operational reporting capabilities
• Collaborate with data engineers and developers on data mapping, ETL/ELT design, validation, and reporting requirements
• Write and optimize SQL queries for analysis, troubleshooting, and data validation
• Define business logic, metrics, and data definitions for dashboards and reports
• Assist with integration of enterprise and mission-support systems
• Define and support UAT scenarios, test cases, and business validation criteria
• Validate delivered solutions against mission and operational requirements
• Maintain requirements, process maps, data dictionaries, traceability matrices, SOPs, and runbooks
• Support stakeholder communication, change management, training, and adoption of new capabilities
• Support data standards, controls, and process consistency with government, program, supplier, compliance, and operations stakeholders
• Identify and communicate risks, dependencies, and issues
• Lead or support cross-functional workstreams and serve as liaison between mission users and technical teams
• Mentor junior team members and support consistent business analysis and documentation practices

Senior Business Systems Analyst – Data Engineer

• Drive the GTM data roadmap to build scalable, durable data products
• Build and maintain key data pipelines and marts powering company-wide GTM metrics, including headcount, quota attainment, and pipeline
• Build reliable dashboards tracking core metrics and delivering insights across the company
• Collaborate with GTM analyst teams to train and enable them on datasets and data tools
• Write documentation and tutorials
• Work across the full analytics stack, from ad hoc analysis and reports to architecting pipelines
• Build semantic models and run evaluations to power AI tools that let sales operators query business data in natural language
• Use AI-assisted development tools while keeping code, models, and documentation clean and maintainable
• Communicate complex data concepts through technical specifications, dashboards, and presentations to align teams on metrics and definitions
• Report to the Director of Business Intelligence as part of a centralized global analytics and data engineering team

Senior Analytics Engineer – GTM

• Drive business impact and better decision making by laying the data foundation for a world-class analytics function
• Own and maintain the data transformation layer
• Design, write, review, and ship SQL models that transform raw data into usable data products
• Work with Data Engineers to add, model, and publish new data sources in the data warehouse
• Monitor the data warehouse and identify opportunities to improve operations, accuracy, quality, coverage, integrity, structure, and usability
• Translate ambiguous business requests into modeled data and establish business rules and edge cases
• Implement measures to improve data quality, lineage, access, and retention across source production databases
• Own the data dictionary and document tables, columns, data flows, definitions, and calculation methodologies
• Diagnose and resolve data incidents
• Review teammates’ code and provide feedback
• Collaborate with Business Analysts, Data Engineers, Data Scientists, and business process owners
• Enable end users to understand and use data effectively
• Improve agent playbooks, documentation, and data warehouse tooling
• Contribute architectural ideas for the data environment and pipelines
• Help establish the Business Analytics Center of Excellence and improve warehouse usability for analysts and AI agents

Data Analytics Engineer

• Build and maintain dbt models from the business vault layer through to the data mart
• Add fields, refine calculations, and extend existing mart models in collaboration with the BI and Enterprise Data teams
• Build new Kimball-style datasets from business vault sources when no new ingestion is required
• Build and maintain AI-ready datasets for internal AI systems, ensuring structured, documented, and reliable data
• Maintain and enrich the data dictionary in OpenMetadata, including definitions, lineage, and field-level documentation
• Partner with business stakeholders to define reporting metrics and translate ambiguous business questions into clear definitions
• Partner with BI Analysts to translate insight needs into modeling requirements
• Build Tableau dashboards and reports for stakeholders, keeping logic in the data layer and Tableau data sources free from complex calculations

• Own client relationships and serve as the trusted point of ownership for delivery and outcomes
• Partner with the Managing Director on account strategy, execution, internal mobilization, and growth opportunities
• Co-create opportunities with clients by connecting business priorities to firm solutions
• Lead executive presentations, read-outs, and strategic conversations with C-suite clients
• Navigate complex client situations and provide constructive, judgment-based guidance
• Own engagement success across 3+ concurrent engagements from scoping through delivery
• Remove obstacles, prioritize competing demands, and make decisions that keep engagements moving
• Manage engagement economics, profitability, scope changes, and delivery risk
• Draft and manage Master Service Agreement, Sales Order, and Change Order documentation and scopes of work
• Lead, delegate to, coach, and develop Engagement Managers, Associates, and Analysts
• Provide direction, feedback, and mentorship to direct reports
• Participate in recruiting
• Shape account targets and growth strategies with senior leadership
• Build trusted advisor relationships with sponsors, C-suite executives, and operating teams
• Identify cross-selling and upselling opportunities
• Develop case studies and represent the firm at networking and industry events
• Expand expertise in a selected industry, functional, or business domain
• Guide teams on approach and quality using technical fluency while relying on specialists for hands-on execution
• Collaborate with data engineers, software engineers, data scientists, and AI engineers
• Stay current with industry trends and contribute to firm strategy and operational excellence initiatives

Principal Analytics Engineer

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure.

Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users.

Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development.

We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you.




APPLYING TO RENDER

We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team.

We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed.

Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time.




ABOUT THE ROLE

We're looking for a Senior/Staff Analytics Engineer to join our growing Data team and lead the evolution of our Analytics Engineering platform. As Render scales, you'll build the foundations that turn raw data into trusted, reusable models for analytics, executive reporting, and AI-assisted decision-making.

In this role, you'll partner closely with analysts, scientists, data engineers, and teams across Product, Engineering, Growth, Go-to-Market, Finance, and other business functions. Analysts and scientists will bring domain expertise and own business logic within their areas; you'll own the technical architecture, modeling standards, and engineering practices that help that work scale reliably.

As a Senior/Staff-level individual contributor, you'll set the technical direction for Analytics Engineering at Render—strengthening data quality, improving the developer experience, and building semantic and context layers that make data easier to discover and use. You'll help teams move faster with consistent metrics and maintainable models they can trust.




WHAT YOU'LL DO

 - Own our Analytics Engineering architecture. Guide the long-term evolution of Render’s Analytics Engineering platform, strengthening foundational models so our data remains trusted, scalable, and ready for AI-assisted analytics.

 - Build trusted, reusable data models. Design, build, and maintain governed dbt models that serve as authoritative sources for business-critical metrics across Product, Engineering, Growth, Go-to-Market, Finance, and other teams.

 - Establish engineering standards. Define and improve practices for data modeling, testing, documentation, version control, CI/CD, and code review. Review high-impact dbt changes and reduce technical debt across the analytics codebase.

 - Enable self-service and AI-assisted analytics. Design and maintain semantic and context layers that make metrics consistent, data discoverable, and analysis reliable for both people and AI tools.

 - Partner closely with analysts and scientists. Help analysts and scientists translate domain-specific business logic into scalable, maintainable warehouse models, moving shared logic out of individual reports and dashboards and into governed datasets.

 - Improve reliability and efficiency. Partner with Data Engineering to strengthen source data quality, warehouse architecture, and BigQuery performance and cost efficiency.

 - Raise the bar for Analytics Engineering. Mentor analysts, scientists, and analytics engineers on dbt development, dimensional modeling, and engineering best practices, and help teams adopt shared standards.




WHAT WE'RE LOOKING FOR

 - 7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, including at least 3 years of hands-on experience running dbt in production.

 - Expert-level SQL skills and a track record of designing and owning scalable Kimball dimensional models.

 - Deep expertise in modern Analytics Engineering practices, including Git, testing, CI/CD, documentation, data contracts, lineage, and governance.

 - Experience building semantic and context layers, trusted metrics, and warehouse architectures that support self-service analytics for humans and AI agents across multiple business domains.

 - Strong understanding of modern cloud data warehouse architecture, performance optimization, and cost efficiency, with experience in platforms such as BigQuery, Databricks, or Snowflake.

 - A track record of establishing technical standards, influencing engineering practices without formal authority, and improving reliability while reducing technical debt.

 - Proven ability to partner closely with analysts, scientists, and business stakeholders to translate requirements into scalable, maintainable data models.

 - Excellent communication skills. You can explain complex technical concepts and tradeoffs to technical and non-technical audiences and build alignment across teams.

 - Experience building data models that connect product usage, acquisition, CRM, and financial data across the customer lifecycle.

 - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate data modeling, testing, documentation, or exploration.




NICE-TO-HAVES

 - Hands-on experience with Render’s analytics stack, including BigQuery, Segment, dbt, and analytics tools such as Metabase or Mixpanel.

 - Experience with developer-focused, product-led, sales-led, or usage-based businesses.

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

If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need.




BENEFITS

 - 4 weeks of paid vacation.

 - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return.

 - Long-term disability, life insurance, and 401K plans.

 - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well.

 - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc.

 - Monthly cell phone and internet subsidy.

 - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders.

 - Continuous learning benefits & related support.

This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization.

Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

We encourage all who are interested to apply. We can't wait to hear from you!

Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view

Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Senior/Staff Analytics Engineer

• Participate in the architectural direction for CNN’s Data Platform
• Own data modeling, schema design, and platform capabilities serving Analytics, Data Science, ML, and AI teams
• Develop, design, and implement CNN’s Data Platform for real-time data use cases
• Mentor junior engineers through code reviews, design sessions, and technical guidance
• Deliver scalable data pipelines for real-time streaming and batch processing
• Drive best practices around security, performance, and reliability for data services
• Contribute to technical roadmap planning and advocate for data platform improvements
• Deliver high-quality, well-tested code
• Improve code, documentation, and operational runbooks with each iteration
• Communicate designs, architectural decisions, and technical tradeoffs to engineers and leaders
• Represent the data platform domain with autonomy
• Evangelize and oversee implementation of data engineering best practices
• Maintain monitoring, alerting, and documentation for long-term system health
• Build solutions powering audience analytics, personalization, and content recommendations for CNN experiences

Analytics Engineer jobs in Canada

Senior Analytics Engineer

Senior Analytics Engineer

Senior Analytics Engineer

Senior Business Systems Analyst – Data Engineer

Senior Analytics Engineer – GTM

Data Analytics Engineer