Data Architect jobs

The difference you will make:

As a member of this team you would be working with talented engineers on building infrastructure to solve cutting edge experimentation problems. The primary focus of this position will be on our platform’s results computation stack, consisting of data pipelines, a grammar for experimentation, and an analysis engine. You will bring a deep understanding of data processing, API design and experimentation methodology to help us reliably and accurately calculate results at scale, and to push the boundaries of what we can learn from experiments. The stack you would be working with consists of technologies like Spark, Trino, Python, and Airflow.

A typical day:

• Work to build, maintain, optimize and extend complex and large scale data processing pipelines.
• Contribute to Airbnb’s library for flexible and extensible on-demand analysis of experiments.
• Partner with teams across the organization to improve the impact of experimentation across the company. Participate in all phases of software development of the overall platform from architecture/design through implementation, testing, and on-call.
• Work closely with Data Science partners to implement sophisticated statistical methodologies into the platform.

• Participate in experiment reviews to understand how our customers use our infrastructure, identify areas for improvement and learn about features rolling out across the company.

Your expertise:

• 9+ years in a hands-on software engineering role, shipping high quality code to production, especially for high scale, distributed systems, data pipelines, and/or analytical libraries.
• Experience with at least one modern, general programming language (e.g. Python, Java)
• Experience with scientific/statistical computation, especially involving online experimentation
• Experience building software with ergonomic interfaces and great developer experience, especially for technical data users (e.g. data scientists).
• Experience with at least one modern “big data” technology (e.g. Spark, Dataflow)
• Strong SQL skills - you should be able to “go deep” when debugging or optimizing.
• [Nice to have] Experience building frameworks which generate data pipelines at scale.
• [Nice to have] Experience with a distributed stream processing framework (e.g. Flink, Kafka, Dataflow)

Offices: United States

The Community You Will Join:

You will join a team dedicated to driving innovation and optimizing our dynamic Marketplace. As a member of the Marketplace Data Science team, you will tackle challenges at the core of our business, including pricing, supply management, and fee strategies. Collaborating with leaders across the company, you will play a key role in shaping the future of our marketplace.

The Difference You Will Make:

As a Staff Data Scientist, you will be responsible for building data products, inference frameworks, and intelligence to enable the growth of our marketplace. Your work will include:

• Specifying and estimating models to determine the impact of supply and demand on marketplace outcomes
• Delivering data and insights to enable the company’s supply growth efforts
• Providing mentorship to other data scientists and exemplifying a high bar for technical excellence

A Typical Day:

• Crafting models: You will develop models to accurately forecast key marketplace metrics, enabling proactive decision-making and strategic planning.
• Advanced causal inference: Utilizing cutting-edge causal inference techniques, you will quantify the impact of changes in supply and demand on the marketplace, informing targeted improvements and interventions.
• Cross-functional collaboration: You will actively collaborate with teams across product, engineering, and operations to integrate data science insights into initiatives aimed at enhancing supply acquisition, retention, and success.
• Stakeholder engagement: You will engage with stakeholders to understand their business objectives and provide data-driven solutions tailored to these goals.

Your Expertise:

• 9+ years of relevant industry experience and a Master’s degree or PhD in a quantitative field
• Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
• Experience with causal inference and machine learning techniques, ideally in a multi-sided platform setting
• Proven ability to succeed in collaborative environments with cross-functional stakeholders and also in independent work environments
• Proven ability to communicate clearly and effectively to audiences of varying technical levels

Offices: United States

The Community You Will Join:

You will join a team dedicated to driving innovation and optimizing our dynamic Marketplace. As a member of the Marketplace Data Science team, you will tackle challenges at the core of our business, including pricing, supply management, and fee strategies. Collaborating with leaders across the company, you will play a key role in shaping the future of our marketplace.

The Difference You Will Make:

As a Senior Data Scientist, you will be responsible for building data products, inference frameworks, and intelligence to enable the growth of our marketplace. Your work will include:

• Specifying and estimating models to determine the impact of supply and demand on marketplace outcomes
• Delivering data and insights to enable the company’s supply growth efforts

A Typical Day:

• Crafting models: You will develop models to accurately forecast key marketplace metrics, enabling proactive decision-making and strategic planning.
• Advanced causal inference: Utilizing cutting-edge causal inference techniques, you will quantify the impact of changes in supply and demand on the marketplace, informing targeted improvements and interventions.
• Cross-functional collaboration: You will actively collaborate with teams across product, engineering, and operations to integrate data science insights into initiatives aimed at enhancing supply acquisition, retention, and success.
• Stakeholder engagement: You will engage with stakeholders to understand their business objectives and provide data-driven solutions tailored to these goals.

Your Expertise:

• 5+ years of relevant industry experience, or 2+ years with a PhD
• Background in economics, statistics, and experimentation. A PhD or Master’s in economics or a related field is valued
• Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
• Experience with causal inference and machine learning techniques, ideally in a multi-sided platform setting
• Proven ability to succeed in collaborative environments with cross-functional stakeholders and also in independent work environments
• Proven ability to communicate clearly and effectively to audiences of varying technical levels

Offices: United States

A Typical Day:

• Inference: Develop and apply causal inference methods, including experimental, econometric regressions, and quasi-experimental methods to measure a wide-range of platform/product impacts.
• AI/ML: Build methods for robust evaluation of ML/AI model efficiency and performance. Ability to identify use-cases for and develop predictive models to classify, segment, and interpret our users’ behavior.
• Optimization: Develop methodologies to explore/simulate the impact of new interventions and develop data products to optimize product/operational strategies.
• Communication: Deliver robust research reports and effective data visualizations. Collaborate with and present to stakeholders to identify opportunities and communicate findings, and drive impact.
• Empowerment: Think strategically about opportunities to improve and scale our brand measurement and customer insights.

Required qualifications

• 9+ years of industry experience in a quantitative analysis role with a Master’s degree in a quantitative field (math / economics / statistics, and etc.), or 6+ years of experience with a PhD degree.
• Strong knowledge of causal inference, experimentation, and statistical modeling.
• Skilled in statistical programming (Python or R) and database usage (SQL)
• Proven ability to communicate clearly and effectively to audiences of varying technical levels
• Ability to translate complex findings and results into compelling narratives that drive impact
• Excellent project management, communication, and teamwork skills
• Payments/Risk Domain expertise is a strong plus

Offices: United States

Senior MTS Software Engineer, Data Platform

Job Type: Full-time

We are seeking Data Platform Software Engineers, not Data Engineers . While familiarity with Spark, Flink, and other tools in the Hadoop environment is a definite advantage, your focus will be on building the data platform rather than just creating data pipelines.

• Independently lead complex, high-impact initiatives across eBay’s Data Platforms, from conception to successful production rollout. You will collaborate with Product Managers to help define the vision for the data platform at eBay.

• Architectural Leadership: Own and evolve the architecture for core data platform systems, ensuring solutions are scalable, secure, maintainable, and in alignment with enterprise standards.

• System Design: Eliminate duplication across systems and ensure clear responsibility boundaries; align systems with business needs and future scalability.

• Engineering Excellence: Champion clean architecture, promote use of modern frameworks, enforce quality gates, and ensure adherence to design patterns and coding standards.

• Lead by Example: Write reference implementations, contribute to core libraries, and conduct in-depth code reviews to influence standards and uplift team capabilities.

• Cost Optimization: Propose and drive engineering solutions that reduce operational overhead, improve resource efficiency, and automate manual processes.

• Framework Development: Find opportunities to build reusable components, services, and frameworks that accelerate feature delivery across the organization

• Modernization: Lead migrations of legacy systems into modern architectures and cloud-native paradigms with minimal disruption and high impact.

• Collaboration: Drive complex technical discussions, build consensus across engineering, product, and operational teams, and ensure smooth delivery of cross-functional projects.

• Documentation & Governance: Create well-structured Architecture Decision Records (ADRs) and contribute to technical documentation and standards.

• Proactively address performance, security, compliance, and future-proofing of solutions while balancing latency, correctness, scale, and cost.

• Raise the engineering bar through design/code reviews, operational excellence (SLOs, observability, incident management), and scalable practices that increase velocity across teams.

• Mentorship: Act as a technical mentor, guiding senior and junior engineers on architecture best practices and advanced problem-solving.

• Introduce AI-first frameworks and reusable components that reduce developer friction and enable faster iteration.

• Automate diagnostics, monitoring, and remediation using intelligent assistants and prediction-based alerting.

• Excellent in interpersonal communication
  

What you bring

• Extensive experience owning large-scale distributed data platforms (multi-PB data, high-throughput streams, global systems).

• Deep systems approach : you anticipate bottlenecks, design for reliability (reprocessing, idempotency, schema evolution), and think holistically across compute, storage, and APIs.

• Excellent decision-making and communication skills , thriving in ambiguity while aligning diverse stakeholders on the right path forward.

• Security and compliance mindset , including data privacy, RBAC/ABAC, encryption, and auditability — with the ability to partner with compliance teams on regulatory requirements.

• Proven leadership in mentoring engineers, shaping team culture, and driving organizational change in engineering practices.

• Growth mindset
  

• High-impact mission : You will build and modernize eBay’s Data Platform, which powers analytics, experimentation, machine learning, personalization, and trust and compliance on a global scale.

• Challenging technical problems : From real-time streaming at scale, to lakehouse correctness, governance, cost and performance optimization, and multi-cloud resiliency.

• Vibrant culture : A collaborative, transparent, and inclusive environment where diverse perspectives are valued, knowledge sharing is encouraged, and every engineer has a voice.

• Flexibility & support : Hybrid/remote-friendly practices, competitive compensation, global benefits ( ), and support for learning resources, conferences, and career development.

• Always-on responsibility with balance
  

Qualifications

• 12+ years of experience in building and operating large-scale distributed systems, with 5+ years as a staff/architect-level technical lead across multiple domains.

• Proven success in driving technical strategy and roadmaps , authoring architecture and technical vision documents, and aligning stakeholders across engineering, product, and compliance.

• Strong foundation in data structures, algorithms, and distributed systems design .

• Proficiency in Java/Python (or equivalent) and in infra-as-code, CI/CD, and containerized environments.

• Hands-on deep internal expertise in several of the following: Kafka/Flink, Spark,, Delta/Iceberg, GraphQL/REST APIs, RDBMS/NoSQL, Kubernetes, Airflow.

• Experience building both streaming and batch data platforms , improving reliability, quality, and developer velocity.

• Demonstrated ability to mentor senior engineers, influence org-wide practices , and make long-term architectural decisions that unlock measurable business outcomes.

• BS/MS in CS or equivalent practical experience.

The base pay range for this position is expected in the range below: