ABOUT KHAN ACADEMY Khan Academy is a nonprofit with the mission to deliver a free, world-class education to anyone, anywhere. Our proven learning platform offers free, high-quality supplemental learning content and practice that cover Pre-K - 12th grade and early college core academic subjects, focusing on math and science. We have over 181 million registered learners globally and are committed to improving learning outcomes for students worldwide, focusing on learners in historically under-resourced communities. OUR COMMUNITY Our students, teachers, and parents come from all walks of life, and so do we. Our team includes people from academia, traditional/non-traditional education, big tech companies, and tiny startups. We hire great people from diverse backgrounds and experiences because it makes our company stronger. We value diversity, equity, inclusion, and belonging as necessary to achieve our mission and impact the communities we serve. We know that transforming education starts in-house with learning about ourselves and our colleagues. We strive to be world-class in investing in our people and commit to developing you as a professional. About the Role We’re looking for a Senior Analytics Engineer I to join Khan Academy’s Analytics Engineering (AE) team. You’ll play a leading role in designing and building the datasets, pipelines, and semantic models that power insights across our organization. You’ll own key areas of our data modeling ecosystem, partner closely with Data Infrastructure (DI), Data Analysts, and Product/Program teams, and help ensure that our data warehouse (BigQuery) and BI layer (Looker) remain reliable, performant, and trusted. This role is ideal for someone who’s deeply experienced in dbt and Looker , enjoys solving complex modeling challenges, and takes ownership of how data flows and scales across the organization. What You’ll Do Design, implement, and optimize dbt models that transform raw event- and entity-level data into analytics-ready datasets. Own and evolve data domains that support reporting across Khan Academy. Develop, document, and test semantic and reporting layers in Looker (LookML). Partner with Analysts to establish consistent metric definitions, reusable data patterns, and shared governance practices. Drive data modeling standards and champion best practices in naming, testing, and schema design. Diagnose and resolve complex data issues, coordinating across Data Infrastructure and Engineering when needed. Mentor Analytics Engineers and Analysts, providing feedback through code reviews and technical guidance. Collaborate with cross-functional teams to identify opportunities to improve data accessibility and reliability. What We’re Looking For Required Skills & Experience: 6+ years of deep, warehouse-centric analytics engineering experience. Expert-level SQL and dbt skills (macros, Jinja, incremental model strategies, schema testing). Deep experience building and maintaining Looker models (LookML, Explores, derived tables, and performance tuning). Proven ability to design scalable, maintainable data models (SCD2, star schemas, bridge tables, data marts). Familiarity with modern data stacks (e.g., BigQuery, Git, and CI/CD practices for testing and deploying data models). Experience orchestrating workflows using tools like Airflow. Strong cross-functional communication skills and ability to influence data decisions across teams. Familiarity with version control and collaborative development (Git, pull requests, and code review). Preferred: Experience with BigQuery specifically. Background in education technology or mission-driven organizations. Demonstrated contributions to data governance, metrics standardization, or semantic modeling initiatives. Our Tech Stack Warehouse: BigQuery Transformation: dbt (open-source) BI / Semantic Layer: Looker Orchestration: Airflow Version Control: GitHub Collaboration: Confluence, Jira, Slack PERKS AND BENEFITS We may be a non-profit, but we reward our talented team extremely well! We offer: Competitive salaries Ample paid time off as needed – Your well-being is a priority 8 pre-scheduled Wellness Days in 2026 occurring on a Monday or a Friday for a 3-day weekend boost Remote-first culture - that caters to your time zone, with open flexibility as needed, at times Generous parental leave An exceptional team that trusts you and gives you the freedom to do your best The chance to put your talents towards a deeply meaningful mission and the opportunity to work on high-impact products that are already defining the future of education Opportunities to connect through affinity, ally, and social groups And we offer all those other typical benefits as well: 401(k) + 4% matching & comprehensive insurance, including medical, dental, vision, and life At Khan Academy we are committed to fair and equitable compensation practices, the well-being of our employees, and our Khan community. This belief is why we have built out a robust Total Rewards package that includes competitive base salaries, and extensive benefits and perks to support physical, mental, and financial well-being. The compensation band for this role is $137,871 - $155,105 USD annually for candidates based in the United States and $186,306 - $209,595 CAD annually for candidates based in Canada. The pay range for this position is a general guideline only. The salary offered will depend on internal pay equity and the candidate’s relevant skills, experience, qualifications, and job market data. MORE ABOUT US Sal’s TED talk from 2011 Sal’s TED talk from 2015 Sal's TED talk from 2023 Our team: http://www.khanacademy.org/about/the-team OUR COMPANY VALUES Live & breathe learners We deeply understand and empathize with our users. We leverage user insights, research, and experience to build content, products, services, and experiences that our users trust and love. Our success is defined by the success of our learners and educators. Take a stand As a company, we have conviction in our aspirational point of view of how education will evolve. The work we do is in service to moving towards that point of view. However, we also listen, learn and flex in the face of new data, and commit to evolving this point of view as the industry and our users evolve. Embrace diverse perspectives We are a diverse community. We seek out and embrace a diversity of voices, perspectives and life experiences leading to stronger, more inclusive teams and better outcomes. As individuals, we are committed to bringing up tough topics and leaning into different points of view with curiosity. We actively listen, learn and collaborate to gain a shared understanding. When a decision is made, we commit to moving forward as a united team. Work responsibly and sustainably We understand that achieving our audacious mission is a marathon, so we set realistic timelines and we focus on delivery that also links to the bigger picture. As a non-profit, we are supported by the generosity of donors as well as strategic partners, and understand our responsibility to our finite resources. We spend every dollar as though it were our own. We are responsible for the impact we have on the world and to each other. We ensure our team and company stay healthy and financially sustainable. Bring out the joy We are committed to making learning a joyful process. This informs what we build for our users and the culture we co-create with our teammates, partners and donors. Cultivate learning mindset We believe in the power of growth for learners and for ourselves. We constantly learn and teach to improve our offerings, ourselves, and our organization. We learn from our mistakes and aren’t afraid to fail. We don't let past failures or successes stop us from taking future bold action and achieving our goals. Deliver wow We insist on high standards and deliver delightful, effective end-to-end experiences that our users can rely on. We choose to focus on fewer things — each of which aligns to our ambitious vision — so we can deliver high-quality experiences that accelerate positive measurable learning with our strategic partners. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, gender, gender identity or expression, national origin, sexual orientation, age, citizenship, marital status, disability, or Veteran status. We value diversity, equity, and inclusion, and we encourage candidates from historically underrepresented groups to apply. As part of this commitment, Khan Academy will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact careers@khanacademy.org

• Enable self-service analytics for all team members by designing clean, intuitive data models and metrics through dbt, empowering employees to make informed, data-driven decisions. • Develop and refine custom data pipelines that ingest data from operational systems to our analytics platform, handling both streaming and batch data using third-party tooling and homegrown solutions. • Maintain and optimize the data platform infrastructure, focusing on data quality, ELT efficiency, and platform hygiene. • Architect and implement key components of the analytics infrastructure, such as BI, semantic layers, and a foundational data warehouse. • Develop and maintain streaming data pipelines from various databases and data sources. • Collaborate across business units to understand data needs and ensure the required data is collected, modeled, and available to team members. • Document best practices and coach/advise other data analysts, product managers, engineers, etc. on data modeling, SQL query optimization & reusability, etc. Keep our data platform tidy by managing roles and permissions and deprecating old projects.

Role Description We are seeking a data-driven BI Engineer to join our team at a high-growth advertising technology company. This role focuses on scaling our reporting infrastructure for advertising performance and billing reconciliation, ensuring that financial and operational data is accurate, automated, and actionable. - Develop robust data pipelines, ensuring data quality and reliability. - Enable efficient data consumption across the organization. - Collaborate closely with cross-functional teams including Product, Engineering, Analytics, and Business stakeholders to deliver high-impact data platforms. The ideal candidate is a proactive problem-solver with strong technical expertise, capable of working with large datasets, modern data architectures, and cloud-based environments. You thrive in fast-paced settings, navigate ambiguity with confidence, and are passionate about turning data into actionable value. Qualifications - Strong experience working with Databricks Lakehouse architecture. - Experience designing and maintaining scalable data pipelines. - Ability to process and model large-scale analytical datasets. - Expert-level SQL development, including: - Window functions - Performance optimization - Complex joins and aggregations - Experience using Jinja SQL templating (dbt or similar frameworks). - Ability to build modular and reusable SQL transformations. Requirements - Exposure to AI-powered data workflows, particularly where AI assists in data processing, enrichment, or anomaly detection. - Integrating LLM APIs (e.g., OpenAI, Anthropic) into data pipelines. - Using AI for: - Automated data classification - Anomaly detection - Data enrichment - Exposure to Model Context Protocol (MCP) or similar approaches to connect AI models with external tools and data sources. Key Responsibilities - Build, maintain, and optimize scalable data pipelines and workspaces within the Databricks environment. - Develop and audit complex reporting models focused on advertising performance metrics and financial billing. - Write high-performance SQL queries and leverage Jinja SQL to create dynamic and reusable transformations. - Design data models that support accurate and actionable business insights. - Collaborate with cross-functional teams to ensure data reliability and reporting accuracy. - Explore and implement basic AI/ML enhancements such as predictive billing models or anomaly detection. - Support automation efforts through CI/CD practices using GitHub and Jenkins. - Maintain clean and well-documented configuration files using YAML/YML. - Continuously improve data workflows for efficiency, scalability, and quality. Benefits - Monetary compensation - Year-end Bonus - IMSS, AFORE, INFONAVIT - Major Medical Expenses Insurance - Minor Medical Expenses Insurance - Life Insurance - Funeral Expenses Insurance - Preferential rates for car insurance - TDU Membership - Holidays and Vacations - Life happens days - Bereavement days - Civil Marriage days - Maternity & Paternity leave - English and Spanish classes - Performance Management Framework - Certifications - TALISIS Agreement: Discounts at ADVENIO, Harmon Hall, U-ERRE, UNID - Taquitos Rewards - Amazon Gift Card on your Birthday - Work-from-home Bonus - Laptop Policy Equal Employment Enroute is committed to providing equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Role Description Build the data foundations of our monetisation platform. Thanks is building a customer-first monetisation platform that delivers growth without compromise – for advertisers, publishers, and customers. We’re hiring a Staff Data Engineer to build our data foundations from the ground up. This is our first dedicated data engineering hire; a senior individual contributor who will design and deliver the data architecture, models and products that will scale the success of Thanks. This role is deeply hands-on, highly influential, and foundational to the future of our engineering and product organisation. - Build the data platform: Design and deliver a scalable platform that serves as the primary engine for the Thanks Network. - Own the models: Responsible for the data science, technical implementation, and performance of our ranking systems. - Build for real-time inference: Own the end-to-end lifecycle of our models – from training and validation to real-time inference. - Unlock model experimentation: Build the framework that allows us to run experiments on our ranking systems. - Own pipelines & observability: Build robust batch and near-real-time pipelines that are resilient and observable. - Enable self–serve analytics: Design clean, trusted datasets and data marts for product, engineering, and commercial teams. - Set the data direction: Define tooling, architecture, and trade-offs as our data needs evolve. - Lead through expertise: Act as the go-to expert for data across the business. Qualifications - Experience operating as a senior, hands-on individual contributor in high-growth environments. - Deep strength in both data engineering and applied data science. - Experience building and operating data pipelines in cloud environments. - Hands-on experience with analytical databases. - Familiarity with streaming or event-driven data architectures. - Comfortable operating as a senior IC in a greenfield environment. - Excellent communication skills and the ability to partner effectively across teams. - Uses AI thoughtfully to augment exploration, modelling, and engineering workflows. - Strong internal drive – cares deeply about performance, correctness, and building systems that last. Requirements - Data Engineering: PySpark, dbt, strong SQL skills (must have). - Data Workflow Pipeline: one of Airflow, Dagster, Step Functions or equivalent (must have, at least 1). - DevOps / DataOps: Terraform, CloudFormation, Azure ARM, Kubernetes (must have, at least 1). - Data Warehouse: Databricks, Snowflake, BigQuery, ClickHouse, Redshift, etc. (must have, at least 1). - Data Catalog / Feature Store: Databricks Unity Catalog, Atlas (nice to have). - Event Streaming: Kafka, Kinesis, or equivalent (nice to have). - Data Analytics / Reporting: Experience working on or supporting reporting functions such as Tableau, Power BI, Superset, etc. (nice to have). - Data QA: Great Expectations, DBT testing, etc (nice to have). Benefits - Foundational ownership: Build and own core data foundations from the ground up. - Impact you can see: Your work directly influences product performance and experimentation. - Strategy meets execution: This is a hands-on role while setting direction for a fast-growing platform. - Growth, without chaos: Work closely with founders and Head of Product in a supportive culture. - Attractive compensation: Including meaningful equity. - Flexibility with intent: Open to exceptional candidates across Australia’s east coast.