Вакансии

-реализовывать высоконагруженные конвейеры обработки данных для обеспечения надежной и бесперебойной репликации данных из ИТ-систем. -реализовывать комплексные задачи по подготовке данных в целевых аналитических хранилищах (DataLake, SandBox, FeatureStore) для построения признаков, необходимых для разработки моделей машинного обучения.

Разрабатывать и исследовать ML-модели для генерации изображений и визуализации интерьерных/строительных решений на основе товаров Лемана ПРО. Проектировать и реализовывать end-to-end пайплайны для PoC: от сбора и подготовки данных до обучения, оценки и демонстрации результатов.

Участвовать в разработке ядра платформы и самых сложных задачах команды. Разбираешься в дата-инфраструктуре: ETL/ELT, DWH и Data Lake, модели данных, витрины, семантический слой.

Тебе предстоит решать исследовательские и прикладные задачи: от анализа данных и разработки метрик до создания, внедрения и сопровождения алгоритмов. Чем предстоит заниматься Анализировать и обрабатывать данные различного объёма и структуры.

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   We’re looking for a Senior Analytics Engineer to join Kraken’s Finance Data Eng & Analytics team within Data Platform. You’ll build trusted financial data products, using automation and AI to reduce manual work and improve the close process. Working at the intersection of data engineering and accounting, you’ll turn complex financial data into reliable pipelines, models and automated reconciliations. You’ll use AI-assisted tools to accelerate development and investigations, keeping financial outputs tested and traceable.   THE OPPORTUNITY - You’ll work closely with Data Engineers, Finance and Platform Accounting to improve reporting and decision-making. Clear communication and collaboration will help you agree priorities, explain findings and drive adoption. - Partner with Finance to understand workflows, identify pain points and translate business needs into practical data and automation solutions. - Build and maintain automated workflows for data preparation, reconciliations, reporting and follow-ups, with clear controls, monitoring and exception handling. - Build intuitive dashboards and visualizations that help stakeholders understand performance, investigate issues and make decisions. - Resolve finance data issues and reconciliation breaks with Finance, Product and Engineering, addressing root causes and communicating progress. - Build scalable, reliable pipelines to collect, transform and curate data from internal platforms and external systems. - Support the design and rollout of a trusted finance data lake, with clear definitions, ownership and quality checks. - Improve data timeliness, enabling near-real-time insights where they add business value. - Evaluate new technologies, including AI-assisted automation, and prototype solutions to Finance needs that can be reliably supported in production.   WHAT YOU BRING - 7+ years of experience in data analytics and data management within financial services or a regulated industry, working directly with Finance teams. - Strong SQL and Python skills, including writing, debugging and maintaining production code. - Solid experience with Git, merge requests, and code reviews, supported by strong software engineering practices, including testing and documentation. - Hands-on experience building and operating pipelines and models using dbt, Spark, Airflow or comparable tools. - Direct experience with finance or accounting data, such as reconciliations, subledgers, cost basis or month-end close, including investigating discrepancies and validating outputs with accounting stakeholders. - A track record of owning pipelines end to end, making sound technical decisions and improving reliability as requirements and systems evolve. - Judgment and autonomy to lead complex work, navigate ambiguity and remain accountable for production outcomes. - Experience supporting recurring financial close activities, combined with a proactive approach to identifying manual processes and replacing them with reliable, sustainable automation. - Excellent communication skills, with the ability to collaborate across Engineering and Finance, explain complex technical issues, articulate financial implications, and recommend actionable solutions.   NICE TO HAVES - Experience with cryptocurrency transaction data and how digital-asset activity flows into financial records and reconciliations. - Experience processing large volumes of financial transactions using distributed frameworks such as Spark or PySpark. Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Brazil; Peru; Colombia; Argentina; Canada; Mexico; Chile Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   We’re looking for a Senior Analytics Engineer to join Kraken’s Finance Data Eng & Analytics team within Data Platform. You’ll build trusted financial data products, using automation and AI to reduce manual work and improve the close process. Working at the intersection of data engineering and accounting, you’ll turn complex financial data into reliable pipelines, models and automated reconciliations. You’ll use AI-assisted tools to accelerate development and investigations, keeping financial outputs tested and traceable.   THE OPPORTUNITY - You’ll work closely with Data Engineers, Finance and Platform Accounting to improve reporting and decision-making. Clear communication and collaboration will help you agree priorities, explain findings and drive adoption. - Partner with Finance to understand workflows, identify pain points and translate business needs into practical data and automation solutions. - Build and maintain automated workflows for data preparation, reconciliations, reporting and follow-ups, with clear controls, monitoring and exception handling. - Build intuitive dashboards and visualizations that help stakeholders understand performance, investigate issues and make decisions. - Resolve finance data issues and reconciliation breaks with Finance, Product and Engineering, addressing root causes and communicating progress. - Build scalable, reliable pipelines to collect, transform and curate data from internal platforms and external systems. - Support the design and rollout of a trusted finance data lake, with clear definitions, ownership and quality checks. - Improve data timeliness, enabling near-real-time insights where they add business value. - Evaluate new technologies, including AI-assisted automation, and prototype solutions to Finance needs that can be reliably supported in production.   WHAT YOU BRING - 7+ years of experience in data analytics and data management within financial services or a regulated industry, working directly with Finance teams. - Strong SQL and Python skills, including writing, debugging and maintaining production code. - Solid experience with Git, merge requests, and code reviews, supported by strong software engineering practices, including testing and documentation. - Hands-on experience building and operating pipelines and models using dbt, Spark, Airflow or comparable tools. - Direct experience with finance or accounting data, such as reconciliations, subledgers, cost basis or month-end close, including investigating discrepancies and validating outputs with accounting stakeholders. - A track record of owning pipelines end to end, making sound technical decisions and improving reliability as requirements and systems evolve. - Judgment and autonomy to lead complex work, navigate ambiguity and remain accountable for production outcomes. - Experience supporting recurring financial close activities, combined with a proactive approach to identifying manual processes and replacing them with reliable, sustainable automation. - Excellent communication skills, with the ability to collaborate across Engineering and Finance, explain complex technical issues, articulate financial implications, and recommend actionable solutions.   NICE TO HAVES - Experience with cryptocurrency transaction data and how digital-asset activity flows into financial records and reconciliations. - Experience processing large volumes of financial transactions using distributed frameworks such as Spark or PySpark.       Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Москва Мы – команда экспертов, объединенных общей страстью к искусственному интеллекту и рекомендательным системам (RecSys). Нашей главной задачей является создание современной, масштабируемой рекомендательной платформы, способной предвосхищать ожидания пользователей, предлагая персонализированные рекомендации на каждом этапе их взаимодействия с экосистемой Сбер. Наши решения охватывают широкий спектр отраслей: от финансов и e-commerce до индустрии развлечений и здравоохранения. Ищем лидера с сильным практическим опытом Data Analyst (DA), который возглавит аналитическую экспертизу Трайба и будет развивать аналитику как продукт — со своими пользователями, стратегией, целями и планом развития. Ключевая задача — превращать данные в инсайты, задавать направления исследований и помогать командам запускать пилоты, приводящие к измеримому бизнес-инкременту. Обязанности ### Вам предстоит: * формировать стратегию развития аналитики Трайба: изучать потребности внутренних пользователей, определять цели и метрики ценности аналитики, выстраивать и приоритизировать план развития совместно с бизнесом и продуктовыми командами * лидировать аналитическую экспертизу: задавать стандарты исследований, расчёта метрик и интерпретации результатов, проводить экспертное ревью, развивать компетенции аналитиков и обмен знаниями между командами * проводить сложные исследования клиентского поведения, потребностей и рекомендательных сценариев; находить точки роста и формировать инсайты для продуктовых и ML-команд * переводить инсайты в проверяемые гипотезы: определять направления дальнейших исследований, оценивать потенциальный эффект и помогать выбирать приоритетные пилоты * обеспечивать аналитическое сопровождение пилотов: совместно с командами определять критерии успеха, проектировать A/B-тесты, анализировать результаты и готовить рекомендации по масштабированию или доработке решений * оценивать инкрементальное влияние решений на бизнес-метрики совместно с бизнес-заказчиками; прослеживать путь от аналитического вывода до принятого решения и измеримого результата * развивать переиспользуемые аналитические продукты: системы метрик, дашборды, инструменты самостоятельного анализа и базу знаний; формировать требования к данным и контролю их качества вместе с инженерами данных * согласовывать приоритеты с продуктовыми, DS/ML- и инженерными командами, представлять выводы руководству и добиваться их применения в продуктовых решениях. Требования * опыт в роли Data Analyst (от 4х лет) или продуктового аналитика: самостоятельное ведение сложных задач от постановки бизнес-вопроса до выводов и рекомендаций * уверенное владение SQL и Python для работы с данными, опыт создания визуализаций и дашбордов в BI-инструментах * знание математической статистики и практический опыт A/B-тестирования, сегментации, когортного и регрессионного анализа; умение оценивать инкрементальный эффект и корректно интерпретировать ограничения результатов * умение связывать поведение пользователей и качество рекомендаций с продуктовыми и бизнес-метриками, находить точки роста и формулировать проверяемые гипотезы * продуктовый подход к аналитике: умение выявлять потребности внутренних пользователей, определять ценность аналитических решений, формировать цели и расставлять приоритеты * способность выступать экспертным лидером: аргументировать методологические решения, повышать качество работы коллег и согласовывать действия нескольких команд * умение ясно объяснять результаты исследований бизнесу и руководству, договариваться с заинтересованными сторонами и работать в условиях неопределённости * способность разбирать аналитические исследования и профессиональные материалы, в том числе на английском языке. **Будет преимуществом:** * опыт руководства или функционального лидирования команды аналитиков: постановка задач, приоритизация, наставничество и развитие сотрудников * опыт построения аналитической функции, формирования её стратегии или развития аналитики как внутреннего продукта * опыт работы с рекомендательными системами, поиском, ML-продуктами, а также в электронной коммерции или стриминговых сервисах * опыт работы с Big Data, в том числе Spark, и автоматизации аналитических процессов * опыт анализа клиентского пути (CJM) и UX-исследований; профильное образование в IT, математике, Data Science или смежных областях. **Технологии и инструменты:** SQL, Python, Pandas, Tableau / Superset / Amplitude, PySpark, Airflow. Для анализа клиентского пути и UX — Figma, Miro, Hotjar. Условия * комфортный современный офис рядом с м. Кутузовская * формат работы – офис * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Глубокое понимание S3/Object Storage и distributed storage architecture.

Роль объединяет анализ больших данных, ETL и описание взаимодействия систем. — Python, SQL, реляционные базы, статистика и вероятность.

• Разработка нового проекта федерального масштаба (информационная система) с нуля; • Поддержка и развитие существующих информационных систем;

- Функциональное тестирование платформы OpenMetadata. - Проверка процессов сканирования источников данных (ingestion), профилирования данных, управления тегами и глоссариями.

Вести аналитическое направление как единую продуктовую линейку: ИИ-аналитика по бюджетным данным, перенос отчётности на портал, новые разделы Цифрового паспорта, сводная аналитика для государственных заказчиков. Держать границу продукта: что входит в платформу, а что продаётся отдельно — ваше предложение и ваша аргументация перед руководством.

- обеспечивать стабильную работу инфраструктуры данных и сопровождать существующие решения. - администрировать Linux-системы, разбираться в технических проблемах и устранять инциденты.

Задачи: — писать на Python и PostgreSQL backend часть веб-приложения. Требования: — опыт разработки бекенда на Python; — опыт работы с базами данных; — знание классических алгоритмов и структур данных; — будет плюсом: знание принципов машинного обучения, компьютерного зрения, Airflow, Linux, Docker, опыт веб-разработки на JS, написания интерфейсов для получения данных, опыт оптимизации баз данных. Условия: — конкурентный уровень заработной платы; — гибридный формат работы, возможность полной удалённой работы; — система премирования за научные достижения, публикацию статей, регистрацию патентов и выступления на конференциях; — «Лекторий» с приглашёнными экспертами и специалистами, делящимися профессиональным опытом; — внутренняя программа поддержки инноваций; — медицинская страховка, включающая стоматологию, госпитализации, международные путешествия; — льготное страхование членов семьи.

• Функциональное тестирование платформы OpenMetadata. • Проверка процессов сканирования источников данных (ingestion), профилирования данных и управления тегами и глоссариями.

Сбор данных из внутренних сервисов, LLM Gateway, GitLab, Jira, логов AI-агентов и других источников. Проектирование и наполнение баз данных и аналитических витрин для оценки использования CodeGen-платформы.

Location: San Francisco, CA, USA About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring a Staff AI/ML Engineer on our Lending and Cashflow team to lead the modeling behind cash flow underwriting and surface member insight: using members' transaction and deposit data to make fair, accurate credit decisions for people that traditional credit scores often miss. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into the credit decisions behind products like MyPay, Instant Loans, and SpotMe. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters, and you'll set the technical direction for how Chime underwrites with cash flow data. In this role, you can expect to Lead the design, training, and deployment of deep learning and classical ML underwriting models that turn members' transaction and cash flow data into credit decisions, from approval and line assignment to loss forecasting Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Set the technical roadmap for Lending ML and raise the bar across the team through design reviews, mentorship, and shared standards for model development, validation, and governance Help identify where AI/ML creates measurable impact for members — and where a simpler answer is the better one To thrive in this role, you have A track record of leading the design and deployment of deep learning models in production, including multi-quarter initiatives that span teams, with a solid grasp of architecture choice, training dynamics, and evaluation, and the judgment to make model design choices Solid machine learning fundamentals: classical modeling, evaluation design, and knowing which metric actually answers the question in front of you Hands-on experience across the end-to-end ML lifecycle — training, experimentation, optimization, deployment, and monitoring Comfort with messy real-world data, including label definition, leakage, class imbalance, and train/serve skew Strong proficiency in Python and SQL, with deep learning frameworks such as PyTorch and distributed compute such as Spark or PySpark Working knowledge of modern ML infrastructure — AWS and tools such as SageMaker, Airflow, Kafka, Redis, and Snowflake — and an MLOps mindset for keeping production systems healthy The ability to operate independently in ambiguous environments, influence technical direction beyond your own team, and explain model decisions clearly to engineers, risk partners, and senior leaders Nice-to-have Experience in either of these is a plus: Credit or underwriting models, and familiarity with model governance, explainability, and fairness requirements, such as adverse action reason codes and fair lending testing Cash flow or alternative-data underwriting: building credit features from bank transaction data, such as income and expense detection, balance trends, and transaction categorization Deployed transformer models in production #LI-Onsite #LI-DA1 Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $246,000 — $340,000 USD A little about us At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members. We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential. Because if we don't—who will? *Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC. What we offer for our full-time, regular employees 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees. ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life. 🏝 Generous vacation policy and company-wide paid days off 🫂 1% of your time off to support local community organizations of your choice 👟 Annual wellness stipend to use towards eligible wellness related expenses 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents 👪 Access to family planning reimbursement 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com . To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice .

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Data Engineer II to join our Engineering team, with a high sense of ownership who is excited about our mission, eager to learn and teach others, and can deliver across the tech stack. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python and SQL in AWS. Where you will work: This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Build, optimize, and maintain data pipelines that power our business Define and build out abstracted reusable data sets to be used for Business Intelligence, Marketing, and Data Science Research Design, build, and evangelize a federated data validation framework to be used to monitor potential data inconsistencies Protect our users’ privacy and security through best practices The ideal candidate has: 2+ years of software/data engineering experience (distributed data processing, data warehousing, data governance, Big Data, data variance, data privacy, and data quality). Expertise in SQL and Python Expertise in building scalable data pipelines, query optimization, data modeling, and defining reusable datasets Experience working with orchestration tools (especially Airflow), databases (especially PostgreSQL), data warehouses (especially Snowflake) Familiarity with SQL tuning, medallion/event-driven architectures, and telemetry. Familiarity with healthcare or insurance Familiarity with data security and HIPPA compliance A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time. What you'll get here: You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Postgres/SQL, Snowflake, Python, AWS, Terraform, Argo, Airflow, Spark, DuckDB, Iceberg, Airbyte, DBT, ElasticSearch (aka OpenSearch), OpenTelemetry, Looker This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare. Compensation Transparency: The target salary range for this position is $ 138,000 - $160,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .