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Elastic

Principal Analytics Engineer

Elastic · United States

  • Hybrid
  • Full-time
  • CA$193,800 / year
  • United States

Job highlights

  • Lead analytics engineering for marketing AI system.
  • Design and build BigQuery and dbt infrastructure.
  • Develop semantic layers for AI data interaction.
  • Integrate customer journey signals from various sources.
  • Partner with teams and mentor other engineers.

About the role

About Elastic

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

The Role

Our Marketing organization is building an AI-powered intelligence system to drive strategy, insights, and revenue. We are looking for a Principal Analytics Engineer to lead the design and build of this foundation. This role is about more than just writing code—it’s about creating the semantic blueprint for how Elastic understands and interacts with its business data. You will synthesize complex data streams into a unified, high-fidelity system that serves as the "source of truth" for the entire customer journey. By engineering a structured knowledge layer, you will enable Elastic to scale Go-To-Market (GTM) efforts in a world where data must be optimized for human reporting, predictive science, and conversational AI alike.

What You Will Be Doing

  • Architect the Foundation: Design and build the core BigQuery and dbt infrastructure that powers Elastic’s marketing intelligence, transforming raw signals into high-fidelity, agent-ready data products.
  • Enable AI & Agents: Develop the semantic layer and structured knowledge base that allows AI agents to accurately "talk" to our business data and reason through complex performance questions.
  • Map the Journey: Integrate disparate signals across digital, product, and sales into a unified lifecycle model that tracks the customer’s path from discovery to revenue.
  • Scale through Partnerships: Partner with Enterprise, Product, Sales, and Finance teams to align on shared metrics while mentoring other engineers to uphold high standards for our data foundation.

What You Bring

  • Data-as-a-Product: You treat data as a high-value product. You are dedicated to the user experience of data—ensuring it is discoverable and reliable for both human teammates and AI agents.
  • Technical Proficiency: Deep experience with BigQuery, dbt, and semantic layers (e.g., dbt Semantic Layer, Vortex AI). You have a proven ability to apply automation or LLM-assisted workflows to the data modeling lifecycle.
  • Architectural Design: Ability to build complex, interconnected systems by starting with the desired outcome and working backward. You enjoy creating extensible frameworks that empower others to innovate.
  • Systems & Design Thinking: The ability to look at a complex web of data and see the underlying architecture required to make it simple and extensible.
  • Collaborative Communication: A track record of "translating" technical debt into business value and coaching peers through complex architectural hurdles.
  • Operational Excellence & Governance: You treat data as infrastructure. You have deep experience implementing data contracts, automated quality monitoring (DQM), and governance frameworks that ensure metrics remain consistent, secure, and reliable across the enterprise.

Bonus Points

  • GTM Fluency: A strong understanding of Go-To-Market mechanics—knowing how technical data structures translate into business-critical concepts like customer acquisition, attribution, and revenue.
  • Marketing Science Foundations: Familiarity with Marketing Mix Modeling (MMM), causality, or incrementality analysis to help the business understand the true ROI of different channels.
  • Privacy & Ethics: Understanding of GDPR/CCPA compliance and how to manage data privacy and consent within a marketing stack, especially when training AI models.
  • Identity Resolution: Proven experience with Identity Stitching or Customer 360 frameworks to unify anonymous digital signals with known customer records.
  • AI Production Scaling: Experience moving AI models or agentic workflows from experimental pilots into standardized, production-level deployments.

Additional Information - We Take Care of Our People

As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do. We strive to have parity of benefits across regions, and while regulations differ from place to place, we believe taking care of our people is the right thing to do.
  • Competitive pay based on the work you do here and not your previous salary
  • Health coverage for you and your family in many locations
  • Ability to craft your calendar with flexible locations and schedules for many roles
  • Generous number of vacation days each year
  • Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
  • Up to 40 hours each year to use toward volunteer projects you love
  • Embracing parenthood with a minimum of 16 weeks of parental leave

Security & Privacy Responsibilities

Take ownership of protecting the confidentiality, integrity, and availability of organizational data and systems by following applicable privacy and security policies, standards, and procedures. Ensure that all individual contributions follow Elastic’s Secure Software Development Framework (SSDF). Proactively participate in mandatory role-based training to ensure personal technical execution consistently aligns with the highest standards of data protection, data privacy, and system resilience.

Equal Opportunity Employer

Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email candidate_accessibility@elastic.co. We will reply to your request within 24 business hours of submission.

Federal Employment Laws

Applicants have rights under Federal Employment Laws and can view the following posters linked below:
  • Family and Medical Leave Act (FMLA) Poster
  • Employee Polygraph Protection Act (EPPA) Poster

Export Controls

Elasticsearch develops and distributes technology and information that is subject to U.S. and other countries’ export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Syria, or Russia, including the Ukrainian territories annexed by Russia (The Crimea region of Ukraine, The Donetsk People's Republic (DNR), The Luhansk People's Republic (LNR), Kherson or Zaporizhzhia). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic.

Compensation

Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched Registered Retirement Savings Plan (RRSP) with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $154,000—$243,600 CAD.

Vacancy Status

This is a posting for an existing vacancy. We are actively seeking to fill this position with a qualified candidate.

Equal Opportunity and Inclusion

Different people approach problems differently. We need that. Elastic is an equal opportunity/affirmative action employer committed to diversity, equity, and inclusion. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation. We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email candidate_accessibility@elastic.co. We will reply to your request within 24 business hours of submission.

Federal Employment Rights

Applicants have rights under Federal Employment Laws, view posters linked below:
  • Family and Medical Leave Act (FMLA) Poster;
  • Equal Employment Opportunity (EEO) Poster;
  • and Employee Polygraph Protection Act (EPPA) Poster.

Skills & topics

  • Analytics Engineer
  • Data Engineering
  • BigQuery
  • dbt
  • Semantic Layer
  • AI
  • Machine Learning
  • Marketing Technology
  • Data Architecture
  • Data Modeling
  • Go-To-Market
  • Cloud Data Warehouse
  • ETL
  • Data Governance
  • Data Quality

How to get hired

  • Tailor your resume: Highlight experience with BigQuery, dbt, and semantic layers relevant to AI and marketing data.
  • Showcase architectural skills: Emphasize your ability to design complex, extensible data systems from desired outcomes.
  • Demonstrate data-as-a-product thinking: Detail how you ensure data discoverability, reliability, and usability for humans and AI.
  • Prepare for technical and behavioral questions: Be ready to discuss your approach to data governance, automation, and collaborative problem-solving.

Technical preparation

Master BigQuery SQL and performance tuning.,Become expert in dbt for data modeling.,Build and manage semantic layers for AI.,Automate data workflows with scripting/LLMs.

Behavioral questions

Describe a complex data architecture you designed.,How do you translate technical debt into business value?,Share an experience mentoring engineers on data standards.,How do you ensure data reliability and discoverability?

Frequently asked questions

What are the key technologies for a Principal Analytics Engineer at Elastic?
The Principal Analytics Engineer role at Elastic heavily utilizes BigQuery and dbt for data infrastructure and modeling. Experience with semantic layers, such as the dbt Semantic Layer or Vortex AI, is also crucial. Familiarity with automation and LLM-assisted workflows in data modeling is a strong plus.
How does Elastic approach data privacy and ethics in this role?
Elastic emphasizes data privacy and ethics, requiring an understanding of GDPR/CCPA compliance. The role involves managing data privacy and consent within the marketing stack, especially for AI model training. Security and privacy responsibilities include protecting data confidentiality, integrity, and availability, and adhering to Elastic's Secure Software Development Framework.
What is the typical salary range for a Principal Analytics Engineer at Elastic?
The typical starting salary range for this role at Elastic is between $154,000 and $243,600 CAD. This is base salary only, and actual compensation may vary based on experience, location, and other factors. Employees may also be eligible for Elastic's stock program.
Does Elastic offer remote work opportunities for a Principal Analytics Engineer?
Elastic is a distributed company and offers flexible locations and schedules for many roles, suggesting that remote or hybrid arrangements may be possible for a Principal Analytics Engineer. However, specific work arrangements are often role-dependent and can be clarified during the application process.
What does 'Data-as-a-Product' mean in the context of this Principal Analytics Engineer role?
In this role, 'Data-as-a-Product' means treating data with the same rigor as a software product. It involves ensuring data is discoverable, reliable, and user-friendly for both human analysts and AI agents, focusing on the end-user experience and data quality.
What are the 'Bonus Points' for the Principal Analytics Engineer position at Elastic?
Bonus points for this role include GTM (Go-To-Market) fluency, familiarity with marketing science foundations like MMM or incrementality analysis, understanding of privacy and ethics (GDPR/CCPA), experience with identity resolution or Customer 360 frameworks, and experience scaling AI models into production.
How can I request an accommodation during the application process at Elastic?
To request an accommodation during the application or recruiting process at Elastic, you should email candidate_accessibility@elastic.co. They will respond to your request within 24 business hours of submission.