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Whatnot

<div>
 
 
 🚀 Join the Future of Commerce with Whatnot!
 
 
 
 
 Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 
 
 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
 
 
 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
 
 
 
 💻 Role
 
 
 
 Data is crucial to Whatnot&rsquo;s mission to bring people together through commerce.
 
 
 As our newest
 
 Data Engineer
 
 , you&rsquo;ll build and scale the systems that power data-driven decisions across the company. You&rsquo;ll work directly with stakeholders across the business &ndash; such as product, sales, marketing, finance, and trust teams &ndash; to design reliable data architectures, ship resilient pipelines, and create the foundational data products that power Whatnot&rsquo;s internal and external growth.
 
 
 
 On Any Given Day, You Will
 
 
 
 <ul>
 <li>
 Own data architecture end-to-end. Define how we capture, model, and serve critical business data&mdash;then implement it in production. You&rsquo;ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
 </li>
 <li>
 Build mission-critical pipelines. Develop and operate streaming and batch data workflows that process high-volume events across multiple domains&mdash;user activity, transactions, experimentation, marketing performance, and operational telemetry&mdash;with tight guarantees for latency, completeness, and accuracy.
 </li>
 <li>
 Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and real-time applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
 </li>
 <li>
 Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
 </li>
 <li>
 Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
 </li>
 <li>
 Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, low-latency data through semantic layers, APIs, and real-time query systems.
 
 
 </li>
 </ul>
 Due to the cross-functional nature of this role, candidates will be matched to multiple teams based on need and experience, including product, analytics, or data platforms teams.
 
 
 
 👋 You
 
 
 
 People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
 
 
 <ul>
 <li>
 Have 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
 </li>
 <li>
 Can design and implement data models using dimensional, Data Vault, or ledger-style techniques that support analytical and transactional workloads.
 </li>
 <li>
 Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
 </li>
 <li>
 Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
 </li>
 <li>
 Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
 </li>
 <li>
 Enjoy partnering across disciplines&mdash;engineering, product, analytics&mdash;to translate messy business requirements into elegant data systems.
 </li>
 <li>
 Thrive as a self-starter in a fast-moving environment, owning both the technical design and the operational outcomes of your work.
 
 
 </li>
 </ul>
 If designing the data backbone that powers Whatnot&rsquo;s growth, insights, and product innovation excites you, we&rsquo;d love to meet you.
 
 
 
 We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
 
 
 
 
 💰Compensation
 
 
 
 
 For Full-Time (Salary)
 
 
 
 
 US based applicants:
 
 $180,000/year to $260,000/year + benefits + equity.
 
 
 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
 
 
 
 🎁 Benefits
 
 
 
 <ul>
 <li>
 Generous Holiday and Time off Policy
 </li>
 <li>
 Health Insurance options including Medical, Dental, Vision
 </li>
 <li>
 Work From Home Support
 </li>
 <ul>
 <li>
 Home office setup allowance
 </li>
 <li>
 Monthly allowance for cell phone and internet
 </li>
 </ul>
 <li>
 Care benefits
 </li>
 <ul>
 <li>
 Monthly allowance for wellness
 </li>
 <li>
 Annual allowance towards Childcare
 </li>
 <li>
 Lifetime benefit for family planning, such as adoption or fertility expenses
 </li>
 </ul>
 <li>
 Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
 </li>
 <li>
 Monthly allowance to dogfood the app
 </li>
 <ul>
 <li>
 All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
 </li>
 </ul>
 <li>
 Parental Leave
 </li>
 <ul>
 <li>
 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
 </li>
 </ul>
 </ul>
 
 
 💛 EOE
 
 
 
 
 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
 
 
 Compensation Range: $180K - $260K
 
 
</div>

Data Engineer

Incedo Inc.

<div>
 
 Incedo Inc. is a high-growth Digital, Data and AI Transformation Specialist firm headquartered in New Jersey. We
 
 
 are a long-term strategy execution partner for Fortune 500 enterprises, operating at the intersection of business
 
 
 and technology across Banking &amp; Payments, Wealth Management, Telecom, Hi-Tech, and Life Sciences.
 
 
 We are building Incedo 4.0 - an AI-native, execution-focused, founder-led organization designed for scale, speed,
 
 
 and long-term impact.
 
 
 Incedo delivers ROI from AI @ Scale through the &ldquo;Power of 3&rdquo;:
 
 
 &bull; Deep domain expertise
 
 
 &bull; AI &amp; Data capabilities
 
 
 &bull; Engineering &amp; Operations excellence
 
 
 
 
 
 
 Job Title: Sr.Data Engineer&ndash; AWS &amp; Streaming
 
 
 
 
 Location
 
 : Fort Mill, SC or New York City, NY (Hybrid)
 
 
 
 
 
 Role Summary:
 
 
 We are seeking a Mid&ndash;Senior Data Engineer with strong expertise in AWS-based data engineering, real-time streaming technologies, and enterprise-grade data quality frameworks. The ideal candidate will design, build, and optimize scalable batch and streaming data pipelines, implement robust data validation and monitoring processes, and support mission-critical analytics platforms.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Develop and maintain scalable ETL/ELT pipelines using AWS Glue, PySpark, and Python
 </li>
 <li>
 Build event-driven workflows using AWS Lambda
 </li>
 <li>
 Design and manage real-time streaming solutions using Kafka, KSQL, and Apache Flink
 </li>
 <li>
 Implement and enforce comprehensive data quality frameworks, including validation, profiling, monitoring, and reconciliation
 </li>
 <li>
 Optimize data processing performance, scalability, reliability, and cost in cloud environments
 </li>
 <li>
 Collaborate with cross-functional teams to deliver reliable, production-grade data platforms and ensure data integrity across the pipeline
 </li>
 </ul>
 
 
 
 
 
 Required Skills:
 
 
 <ul>
 <li>
 Strong hands-on experience with Python and PySpark
 </li>
 <li>
 Proven expertise in AWS Glue, Lambda, and other cloud-native data services
 </li>
 <li>
 Solid experience with the Kafka ecosystem (topics, partitions, consumer groups, streaming patterns)
 </li>
 <li>
 Demonstrated experience building and supporting data quality frameworks (validation rules, reconciliation checks, profiling, anomaly detection)
 </li>
 <li>
 Strong understanding of distributed data processing and scalable architecture patterns
 </li>
 </ul>
 
 
 
 
 
 Good-to-Have Skills:
 
 
 <ul>
 <li>
 Experience with Apache Flink for real-time stream processing and stateful computations
 </li>
 <li>
 Knowledge of KSQL or other streaming SQL engines
 </li>
 <li>
 Exposure to CI/CD pipelines, IaC (Terraform/CloudFormation), and DevOps practices
 </li>
 <li>
 Familiarity with data lake/lakehouse architectures and table formats such as Iceberg, Delta, or Hudi
 </li>
 <li>
 Experience working in enterprise or financial data environments
 </li>
 </ul>
 
 
 
</div>

Senior Data Engineer

BetterUp

<div>
 
 Let&rsquo;s face it, a company whose mission is human transformation better have some fresh thinking about the employer/employee relationship.
 
 
 
 We do. We can&rsquo;t cram it all in here, but you&rsquo;ll start noticing it from the first interview.
 
 
 Even our candidate experience is different. And when you get an offer from us (and accept it), you get way more than a paycheck. You get a personal BetterUp Coach, a development plan, a trained and coached manager, the most amazing team you&rsquo;ve ever met, and most importantly, work that matters.
 
 
 
 Join us and we promise you the most intense and fulfilling years of your career, doing life-changing work in a fun, inventive, soulful culture.
 
 
 
 If that sounds exciting&mdash;and the job description below feels like a fit&mdash;we really should start talking.
 
 
 
 We are a hybrid company with a focus on in-person collaboration when necessary. Employees are expected to be available to work from one of our office hubs at least two days per week, or eight days per month. Our US hub locations include: Austin, TX; New York City, NY; San Francisco, CA; and the Washington, DC metro area. Please ensure you can realistically commit to this structure before applying.
 
 
 
 
 The Opportunity
 
 
 
 BetterUp&rsquo;s GTM Data &amp; Operations team is investing in the infrastructure, intelligence, and automation that powers our go-to-market engine. As an AI / Data Engineer (P3), you will sit at the intersection of data engineering and applied AI&mdash;building the pipelines, models, and systems that help our Sales, Marketing, and Customer Success teams move faster, make smarter decisions, and drive measurable business impact. This is a high-impact role for someone who thrives when technology and strategy meet.
 
 
 
 What You&rsquo;ll Do
 
 
 
 
 Data Engineering &amp; Infrastructure
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable data pipelines that serve clean, reliable data across the GTM stack.
 </li>
 <li>
 Own and evolve our data warehouse architecture (Snowflake) to support GTM analytics, reporting, and AI workloads.
 </li>
 <li>
 Establish and enforce data quality standards, documentation practices, and governance frameworks to ensure trustworthy data at scale.
 </li>
 <li>
 Develop and maintain dbt models, SQL transformations, and Python scripts that power self-serve reporting and downstream analysis.
 </li>
 <li>
 Define and track key GTM metrics, ensuring consistent definitions and reliable data pipelines that support executive and board-level reporting.
 
 
 </li>
 </ul>
 
 Applied AI for GTM
 
 
 
 <ul>
 <li>
 Develop and deploy AI tools for high-impact GTM use cases including lead scoring, pipeline forecasting, churn prediction, and customer segmentation.
 </li>
 <li>
 Partner with Sales, Marketing, and RevOps stakeholders to identify where AI can automate workflows, surface insights, and unlock new capacity.
 </li>
 <li>
 Integrate LLMs and generative AI tooling into GTM systems to streamline operations and accelerate decision-making.
 </li>
 <li>
 Measure and iterate on created systems, translating outputs into actionable tools that are accessible to non-technical stakeholders.
 </li>
 <li>
 Lead cross-functional efforts to integrate AI into core GTM workflows, ensuring adoption across direct and neighboring teams.
 </li>
 <li>
 Coach teammates through AI adoption, helping them build new capabilities and overcome resistance to change.
 
 
 </li>
 </ul>
 
 If You Have Some or All of the Following, Please Apply
 
 
 
 
 Required
 
 
 
 <ul>
 <li>
 3&ndash;5 years of experience in data engineering, analytics engineering, GTM engineering or applied AI roles.
 </li>
 <li>
 Strong proficiency in Python and SQL.
 </li>
 <li>
 Experience building and maintaining data pipelines, reverse ETL workflows and working with modern cloud data warehouses (Snowflake, BigQuery, or Redshift).
 </li>
 <li>
 Familiarity with agentic coding tools (Claude Code, Cursor, etc.).
 </li>
 <li>
 Familiarity with GTM tools and ecosystems (Salesforce, Hubspot, Clay, etc.).
 </li>
 <li>
 Demonstrated ability to build and deploy models (lead scoring, forecasting, classification) in a business context.
 </li>
 <li>
 Experience integrating data and AI into CRM and/or marketing automation platforms (Salesforce, HubSpot, Marketo, etc.).
 </li>
 <li>
 Familiarity with BI tools such as Looker or Hex for dashboard development and self-serve analytics.
 </li>
 <li>
 Familiarity with software engineering principles and tools (version control, CI/CD, testing, code review, Github etc.)
 </li>
 <li>
 Systems-level thinking with the ability to trace data and logic across multiple platforms (e.g., HubSpot &rarr; Salesforce &rarr; Snowflake &rarr; BI layer) and understand how changes in one system ripple across the stack.
 </li>
 <li>
 Strong communication skills with the ability to translate complex technical work into business impact.
 </li>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Data Science, Engineering, or a related field&mdash;or equivalent practical experience.
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Prior experience in a Revenue Operations or GTM Analytics function at a B2B SaaS company.
 </li>
 <li>
 Hands-on experience building with LLMs or deploying generative AI solutions in a production environment.
 </li>
 <li>
 Hands-on experience with decoupled or "headless" semantic layers (Cube, Snowflake Cortex etc.)
 </li>
 <li>
 Track record of working in a high-growth startup or scale-up environment where priorities evolve quickly.
 </li>
 <li>
 Hands-on experience with dbt for data transformation.
 
 
 </li>
 </ul>
 
 AI at BetterUp
 
 
 
 Our team thrives at the intersection of human expertise and AI capability. As an AI-forward company, adaptation and continuous learning are part of our daily work. We&rsquo;re looking for teammates who are excited to evolve alongside technology&mdash;people who experiment boldly, share their discoveries openly, and help define best practices for AI-augmented work.
 
 
 
 As an AI / Data Engineer, you will be expected to:
 
 
 
 <ul>
 <li>
 Lead cross-functional efforts to integrate AI into core GTM workflows, ensuring adoption across direct and neighboring teams.
 </li>
 <li>
 Set measurable AI improvement objectives based on functional strategy with minimal manager direction.
 </li>
 <li>
 Ensure failed AI experiments generate documented learnings that inform future decisions and prevent rework.
 </li>
 <li>
 Make decisions about AI processes and tools that impact your direct team, neighboring teams, and cross-functional partners.
 </li>
 <li>
 Re-architect team processes to incorporate AI at scale&mdash;automated reporting, intelligent workflow routing, systems building.
 
 
 </li>
 </ul>
 
 During our interview process, you&rsquo;ll have opportunities to showcase how you harness AI to learn, iterate, and amplify your impact. We encourage all candidates to share examples of how they&rsquo;ve used AI tools in their work.
 
 
 
 
 Benefits
 
 
 
 At BetterUp, we are committed to living out our mission every day and that starts with providing benefits that allow our employees to care for themselves, support their families, and give back to their community.
 
 
 <ul>
 <li>
 Access to BetterUp coaching; one for you and one for a friend or family member
 </li>
 <li>
 A competitive compensation plan with opportunity for advancement
 </li>
 <li>
 Medical, dental, and vision insurance
 </li>
 <li>
 Flexible paid time off
 </li>
 <li>
 All federal/statutory holidays observed
 </li>
 <li>
 4 BetterUp Inner Work Days
 </li>
 <li>
 5 Volunteer Days to give back
 </li>
 <li>
 Learning and Development stipend
 </li>
 <li>
 Company wide Summer &amp; Winter breaks
 </li>
 <li>
 Year-round charitable contribution of your choice on behalf of BetterUp
 </li>
 <li>
 401(k) self contribution
 
 
 </li>
 </ul>
 
 We are dedicated to building diverse teams that fuel an authentic workplace and sense of belonging for each and every employee. We know applying for a job can be intimidating, please don&rsquo;t hesitate to reach out&mdash;we encourage everyone interested in joining us to apply.
 
 
 
 BetterUp Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, disability, genetics, gender, sexual orientation, age, marital status, veteran status. In addition to federal law requirements, BetterUp Inc. complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. 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.
 
 
 At BetterUp, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, residence location, as well as market indicators. The range below is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future.
 
 
 
 Base Salary Range For This Role Is
 
 
 
 $133,000- $185,000
 
 
 
 We value your privacy. Your personal data will be processed in accordance with our
 
 
 Privacy Policy
 
 
 . If you have any questions about the privacy of your personal data or your rights with regards to your personal data, please reach out to
 
 
 support@betterup.co
 
 
 
</div>

AI Data Engineer

The Museum of Modern Art

<div>The Museum of Modern Art is seeking an experienced Senior Data Engineer to be the technical owner of our data engineering team and the primary point of contact for departments and data analysts who rely on our data warehouse. This role guides and mentors the data engineers on technical standards and best practices, owns the relationship with stakeholders to make sure the data warehouse meets their needs, and serves as the resident expert on our data&mdash;how it is structured, how it relates, and how it should be used. This role requires a strong technical background, excellent problem-solving skills, and strong communication skills.

Responsibilities:
<ul>
<li>Serves as the technical anchor and mentor for the data engineering team, setting standards, reviewing work, and guiding design and architecture decisions.</li>
<li>Owns the relationship with other departments and data analysts, gathers their data needs, and ensures the data warehouse supports them.</li>
<li>Acts as the subject-matter expert on our data, advising analysts on how data is structured, how sources relate, and how best to query it.</li>
<li>Designs, develops, and maintains the data warehouse in Google Cloud Platform (GCP), ensuring scalability, performance, and reliability.</li>
<li>Builds and manage robust ELT pipelines to extract, transform, and load data from various sources into the data warehouse.</li>
<li>Defines and maintains data models that make data consistent and easy to understand for analysts and business users.</li>
<li>Manages and maintains databases, including MS SQL Server and PostgreSQL, ensuring data integrity and security.</li>
<li>Develops and maintains small software applications to support data management tasks and improve operational efficiency.</li>
<li>Collaborates with stakeholders to gather data requirements and translate them into technical solutions.</li>
<li>Troubleshoots data-related issues and provides timely solutions to ensure data availability and accuracy.</li>
<li>Stays up-to-date with the latest data engineering technologies and best practices, and shares them with the team.</li>
<li>Performs any other duties reasonably related to the functions described above.</li>
</ul>
Requirements:
<ul>
<li>Bachelor's or Master's degree in Computer Science or a related field.</li>
<li>Minimum of four years of experience as a Data Engineer with a strong understanding of data warehousing concepts and best practices.</li>
<li>Ability to guide and mentor other engineers and influence technical direction.</li>
<li>Proven experience partnering with analysts and stakeholders to understand their needs and translate them into data solutions.</li>
<li>Strong data modeling skills and the ability to explain how data relates and how it should be used.</li>
<li>Hands-on experience with GCP cloud services, including BigQuery, Cloud Storage, and Dataflow.</li>
<li>Proficiency in SQL and experience with database management systems such as MS SQL Server and PostgreSQL.</li>
<li>Experience building and maintaining ETL pipelines using tools like Apache Airflow or Google Cloud Composer.</li>
<li>Proficiency with Python and pandas.</li>
<li>Experience with other programming languages and paradigms such as C#, nodeJS and Ruby.</li>
<li>Knowledge of managing Linux and Windows servers.</li>
<li>Experience with data modeling and data visualization tools.</li>
<li>Experience with software development methodologies such as Agile.</li>
<li>Familiarity with version control systems like Git.</li>
<li>Excellent problem-solving and analytical skills.</li>
<li>Strong communication and collaboration skills.</li>
</ul>
Reports to: Director of Engineering

Salary Range: Minimum of $140,000 to a maximum of $160,000 per annum

Application instructions: To apply, please visit MoMA Jobs (https://recruiting.ultipro.com/MUS1002MOMA/JobBoard/9dbfa465-a36a-46c3-b31e-4929830ab266/?q=&amp;o=postedDateDesc). Applicants should submit a resume and a cover letter/statement of interest. Applications without cover letters will not be considered.

Equal Employment Opportunity has been, and will continue to be, a fundamental principle at the Museum, where employment is based upon personal capabilities and qualifications without discrimination because of race, color, religion, sex, age, national origin, disability, pregnancy, genetic information, military or veteran status, sexual orientation, gender, gender identity or expression, marital and civil partnership/union status, alienage or citizenship status, creed, genetic predisposition or carrier status, unemployment status, familial status, domestic violence, sexual violence or stalking victim status, caregiver status, arrest or conviction record to the extent required by applicable law, credit history, or any other protected category as established by applicable law, including the New York City Human Rights Law (&ldquo;NYCHRL&rdquo;).
Equal Opportunity Employer 
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.</div>

WW International, Inc. (Weight Watchers)

<div><div><h3 class="jobSectionHeader">WeightWatchers is a global digital health company.</h3>

WeightWatchers is a global digital health company and the world's #1 doctor-recommended, clinically studied behavioral weight health program. For sixty years, we have led the industry by blending science and community to help millions of people build sustainable healthy habits.

As the science of weight health rapidly evolves, so does WeightWatchers. We are redefining the category by developing new clinical pathways for GLP-1 medication access, creating specialized behavioral programs for members on weight-loss medications, and integrating medical care with our proven habit-change framework. By combining these clinical breakthroughs with our digital-first community, we are uniquely positioned to lead the future of weight health care.</div>
We are seeking a seasoned Senior Data Engineer to drive scale, performance, and actionability within our data ecosystem. You will strengthen and scale our Python and Snowflake-based infrastructure, building the core capabilities required to support dynamic analytics and our transition toward more automated, self-service data workflows.

We need an engineer who can adapt to a dynamic product environment, who can ask the 'why' behind the 'what' to ensure we are building the right solutions.
<h3 class="jobSectionHeader">
Key Responsibilities</h3>
<ul><li>Data Enablement: Support the analytics layer by developing core Looker views and building out our agentic AI infrastructure to derive automated self-service capabilities and reduce reporting bottlenecks.</li>
<li>Pipeline Architecture: Design, build, and scale ELT pipelines that are resilient, efficient, and modular.</li>
<li>Cross-Functional Collaboration: Partner with Finance, Product, and Analytics to ensure our data models solve the right problems.</li>
<li>Data Modeling: Build and maintain analytics schemas (including Star Schemas) that abstract complex logic into user-friendly datasets.</li>
<li>End-to-End Ownership: Lead projects from inception to production, taking accountability for data integrity and the trustworthiness of the platform.</li>
<li>Operational Excellence: Monitor production health using monitoring tools (e.g. Datadog, Monte Carlo) ensuring our data ecosystem remains robust and reliable.</li>
<li>Technical Leadership: Act as a technical lead, conduct code reviews, define engineering culture, and champion best practices.</li>
</ul><h3 class="jobSectionHeader">Requirements</h3>
<ul><li>Experience: 5+ years in data engineering, with at least 2+ years focused on distributed, large-scale cloud data warehouses.</li>
<li>Snowflake Expertise: Proven experience with Snowflake performance optimization and cost-governance. Familiarity with Snowflake Cortex/MCP is a plus.</li>
<li>Technical Mastery:</li>
<li><ul><li>Advanced Software Engineering (Python): Deep proficiency in Python, with a focus on writing modular, reusable, and testable code (unit/integration tests) for complex data processing.</li>
<li>Data Modeling &amp; SQL Mastery: Expert-level SQL and a sophisticated understanding of data warehousing methodologies to build performant, scalable analytics layers.</li>
<li>Infrastructure &amp; Automation: Practical experience with modern CI/CD frameworks (e.g., GitHub Actions, Argo CD) to drive engineering velocity and platform stability.</li>
<li>Workflow Orchestration: Expertise in architecting and scaling orchestration-as-code workflows (e.g., Prefect or Airflow) to manage complex dependencies and ensure pipeline resilience.</li>
<li>Observability &amp; Reliability: Deep proficiency in deploying monitoring and alerting frameworks (e.g., Datadog) to maximize system uptime while mitigating alert fatigue.</li>
</ul></li><li>Operational Maturity: Experience managing business-critical production pipelines with a focus on uptime, data quality, and defining SLAs.</li>
<li>Education: BS/MS in Computer Science, Information Systems, or a related technical field.</li></ul><div> 
At WeightWatchers, our mission is to build a worldwide community connected by healthy habits. If that resonates with you, then we would love to talk. WeightWatchers values developing community within our employee population as well. We have a hybrid work environment to allow our employees to find the right work-life balance.

It is our priority to cultivate a diverse and inclusive workplace. We are committed as individuals, as an organization, and as fellow humans, to advocate for and support our employees, our members, and our communities. We are proud to be an equal opportunity employer and we do not discriminate on the basis of sex, race, color, creed, national origin, marital status, age, religion, sexual orientation, gender identity, gender expression, veteran status, or disability.

By agreeing to participate in our process, you agree that any information we collect is subject to our Privacy Policy. 

<div>
<div>Maryland</div>
Under Maryland law, an employer may not require or demand, as a condition of employment, prospective employment, or continued employment, that an individual submit to or take a polygraph examination or similar test. An employer who violates this law is guilty of a misdemeanor and subject to a fine not exceeding $100.</div>
<div></div>
<div>Massachusetts</div>
<div>It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.</div> 
<div>
<div></div><div>WeightWatchers complies with all applicable Rhode Island Workers' Compensation laws (Chapters 29-38 of the R.I. General Laws). Eligible employees are covered by worker's compensation insurance for work-related injuries or illness.</div>
<div></div>
</div><h3 class="jobSectionHeader">RECRUITMENT SECURITY &amp; FRAUD PREVENTION</h3>

At WeightWatchers, we prioritize the security of our candidates. To ensure you are communicating with a legitimate representative of our team, please keep the following security standards in mind:
<ul>
<li>Verified Email Domain: All official correspondence from our recruiting team will originate from an @ww.com email address.</li>
<li>Live Engagement: Our hiring process requires live interaction. We do not conduct interviews or extend employment offers solely through text message, chat apps, or automated email-only exchanges.</li>
<li>Financial Integrity: WeightWatchers will never ask for any form of payment from a candidate. We will never send you a check with instructions to purchase equipment or &quot;start-up kits&quot; on our behalf.</li>
<li>Secure Data Collection: Sensitive personal information (such as banking or identity tax info) is only requested through our official, secure onboarding portal after a formal offer has been extended, never during the interview phase.</li>
</ul>
Stay Vigilant: If you are contacted by someone claiming to represent WeightWatchers and the process deviates from these standards, please do not share any personal information. You can verify any open position by visiting our official careers page at https://job-boards.greenhouse.io/ww</div></div>

Google

<div>
 Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 New York, NY, USA; Mountain View, CA, USA; San Francisco, CA, USA
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
 </li>
 <li>
 1 year of experience designing data pipelines (ETL) and model data.
 </li>
 <li>
 Experience analyzing data and creating reports, and with database query (e.g., SQL) and visualization tools (e.g., Tableau, dashboards).
 </li>
 <li>
 Experience with one or more general purpose programming languages (e.g., Python, C/C++, Java).
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Experience working in a data science environment, supporting feature engineering and model automation needs.
 </li>
 <li>
 Experience working with big data tools, distributed computing and non-relational databases.
 </li>
 <li>
 Structured thinking with ability to easily break down ambiguous problems and propose impactful data modeling designs.
 </li>
 <li>
 Passion for analyzing large and complex data sets and converting them into the information which drive business decisions.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 The GCS Data Science team is working on challenging yet interesting problems for the GCS (Google Customer Solutions) division of Global Business Organization (GBO). Our goal is to build efficient and scalable ML models that help small and midsize businesses around the world to grow their business leveraging the power of Google solutions.
 
 
 The Data Science Engineering (DSet) subteam is responsible for supporting data engineering needs for the GCS Data Science teams including building new data pipelines, automation, observability and reporting tools.
 
 
 As a Data Engineer, you will take on big data challenges in an agile way. In this role, you will use an analytical, data-driven approach to drive a deep understanding of our fast changing business. You will build data pipelines and reporting tools that enable our data scientists, through feature engineering, automated data extracts and wrangling needs, and scaled insights for both the data science team and our users.
 
 
 Google Customer Solutions (GCS) sales teams are trusted advisors and competitive sellers who maintain a relentless focus on customer success by bringing the best Google has to offer to small- and medium-sized businesses (SMBs), which are the backbone of our communities. As a member of our team, you&rsquo;ll have the opportunity to work with company owners and make a real difference in their businesses by helping them grow. Together, we help shape the future of innovation for customers, partners, and sellers...and we have fun doing it.
 
 
 Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
 
 
 US: $106000 - $151000 (USD) + 15% bonus target + equity + benefits
 
 
 
 Responsibilities
 
 
 
 Learn more about benefits at Google .
 
 
 <ul>
 <li>
 Build data pipelines, reports, best practices and frameworks that enable analysts and other stakeholders across the organization.
 </li>
 <li>
 Use feature engineering to support data needs for ML/AI model development and subsequent scaling through ETL pipeline development.
 </li>
 <li>
 Recognize and adopt best practices in developing pipelines, analytical insights including data integrity, test design, analysis, validation and documentation.
 </li>
 <li>
 Design and develop scalable and actionable solutions (dashboards, automated collateral, web applications) that tell a story and provide insights to help our advertisers grow.
 </li>
 <li>
 Work closely with various stakeholders to understand feature/tooling gaps and innovate on behalf of our customers.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Data Engineer, GCS Data Science

Vistar Media

<div>Vistar Media is the home of out-of-home (OOH). As a global ad tech company and the world's largest digital out-of-home (DOOH) advertising marketplace, we offer technology designed to make buying and selling OOH media easier. Our goal is simple: to help the world's marketers leverage OOH's unique ability to motivate and delight.
From strategic partnerships with major media owner networks to executing impactful campaigns with renowned global brands such as Nestl&eacute;, Porsche, Target, and Levi's, our team is filled with passionate, innovative, and collaborative problem solvers, engaging and entertaining consumers like you in the real world. Find your home in out-of-home - find your people at Vistar.
As of January 2025, Vistar Media was acquired by T-Mobile and is now part of T-Mobile Advertising Solutions. By combining our DOOH expertise with T-Mobile&rsquo;s unique customer insights and expansive omnichannel capabilities, we&rsquo;re creating new opportunities to innovate at scale and make a meaningful impact on the future of out-of-home media.
At T-Mobile Advertising Solutions (T-Ads), we're building privacy-first advertising and data products powered by advanced machine learning, large-scale data processing, and cloud technologies. Our proprietary algorithms enable rich consumer insights, intelligent audience solutions, and measurable performance for advertisers while maintaining a strong commitment to consumer privacy.
 
 
We are adding a creative and motivated Senior Data Engineer to join our team, where you&rsquo;ll use modern technologies in big data, cloud, and metadata. As a tech-first product company, the work you do will have a direct impact on our customers and the business. You'll work closely with other engineers, data scientists, and product managers, gaining a holistic understanding of how our systems come together. 
 
We adhere to structured design principles inspired by Lean Development, and we encourage continuous learning and growth. As part of our team, you'll enjoy mentoring, brainstorming, and pairing up to tackle ambitious challenges. Our supportive culture fosters a collaborative atmosphere where everyone can thrive.<ul><li>
Job Responsibilities:<ul><li>
Design and develop data engineering solutions that enable data pipelines, visualization, and analytical tools to support business requirements.</li><li>
Innovate, implement, support, and iterate on scalable big data pipelines and ETL processes.</li><li>
Write robust, efficient, and highly maintainable code in Python, Spark and Scala.</li><li>
Contribute to team knowledge sharing and drive the advancement of new data engineering capabilities.</li><li>
Assist technical, product, and operational leaders in project definition, including estimating, planning, and scoping work to meet objectives.</li><li>
Also responsible for other duties/projects as assigned by business management as needed</li></ul> 
Education and Work Experience:<ul><li>
Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)</li><li>
Acceptable areas of study include Computer Engineering, Computer Science, a related subject area (Required)</li><li>
4-7 years Hands-on implementation and architectural familiarity with streaming data, relational and non-relational databases, and distributed processing technologies. (Required)</li><li>
4-7 years Designing and developing advanced data engineering tasks in Python, SQL, Spark, and related Python libraries (e.g., pandas, scikit-learn, scipy, numpy). (Required)</li><li>
4-7 years Advanced knowledge in building complex data pipelines and cloud bases services (GCP) to support robust and scalable infrastructure (Airflow, Kafka). (Required)</li></ul> 
Knowledge, Skills and Abilities:<ul><li>
Strong background in software engineering, large-scale data and algorithms, cloud architecture, and design thinking. (Required)</li><li>
Experience with production-level engineering around GIS and geospatial data processing. (Preferred)</li><li>
Familiarity with DevOps practices and tools for DataOps.</li><li>
Ability to work quickly and precisely, capturing requirements and designing before implementation.</li><li>
Knowledge of Google BigQuery and tools for solving data-centric problems and working with graph datasets and databases.</li></ul></li></ul>
Base Pay Range: $105,100 - $189,600<div></div> 
Corporate Bonus Target: 15%
The pay range above is the general base pay range for a successful candidate in the role. The successful candidate&rsquo;s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.<div></div> 
At T-Mobile, employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role. Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee&rsquo;s eligible earnings in the prior year. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, https://paylookup.t-mobile.com/paylookup?reqID=REQ353917&para;dox=1
If you&rsquo;re ambitious, highly driven, and interested in making an impact, Vistar is the place for you. Apply to join our team&hellip; we&rsquo;ll see you out there.</div>

Senior Data Engineer, Big Data and Cloud

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