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Senior Data Architect
Оценка ИИПозиция в топовой игровой компании с мировым именем и работой над AAA-проектами. Предлагает работу с передовым стеком технологий и высокую степень ответственности, что отлично подходит для профессионального роста архитектора.
Сложность вакансии
Оценка ИИВысокая сложность обусловлена требованиями к глубокой экспертизе сразу в нескольких областях: проектирование Lakehouse-архитектур, управление данными (Governance) и MLOps. Кандидат должен обладать 7-летним опытом и навыками работы с широким стеком (Snowflake, Databricks, AWS, Kafka).
Анализ зарплаты
Оценка ИИЗарплата для Senior Data Architect в таких технологических хабах, как Остин и Сиэтл, обычно находится в верхнем диапазоне рынка. Учитывая масштаб компании 2K (Take-Two), можно ожидать компенсацию выше среднего, включая бонусы и акции (RSU).
Сопроводительное письмо
I am writing to express my strong interest in the Senior Data Architect position at 2K. With over 7 years of experience in data governance and a proven track record of designing scalable data architectures for analytics and ML, I am confident in my ability to evolve 2K's lakehouse and analytics reference architecture. My expertise in Snowflake, Databricks, and Python, combined with a deep understanding of Kimball and Data Vault modeling, aligns perfectly with your technical requirements.
Throughout my career, I have successfully implemented enterprise-level data governance frameworks and MLOps practices in high-compliance environments. I am particularly excited about the opportunity to standardize Databricks workspaces and integrate data platforms with game analytics for iconic titles like NBA 2K and BioShock. My experience in enforcing security-by-default and ensuring GDPR/CCPA compliance will be an asset to your Core-Tech team in Austin or Seattle.
Составьте идеальное письмо к вакансии с ИИ-агентом
Откликнитесь в 2k уже сейчас
Присоединяйтесь к команде 2K и создавайте архитектуру данных для легендарных игровых франшиз уровня AAA!
Описание вакансии
#LI-Onsite
Who We Are
THIS IS AN ONSITE POSITION in Austin, TX or Seattle, WA
2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K’s portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today’s most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment.
Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K’s portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K, renowned BioShock®️, Borderlands®️, Mafia, Sid Meier’s Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K.
At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don’t meet every requirement for the role. If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply!
What you need
- 7+ years working with data governance platforms (Collibra, Informatica Axon, DataHub) and enterprise governance operating models.
- 5+ years designing data architectures and data models for analytics/ML.
- Proven experience delivering data quality, lineage, and metadata management at scale.
- Bachelor’s or Master’s in Engineering, Computer Science, Mathematics, or related field.
- Deep expertise in data modeling (Kimball, Inmon, Data Vault).
- Strong Python skills, including structured project design and APIs/services with Flask.
- Expert SQL across Snowflake and Databricks.
- Hands-on experience with big data and orchestration tools (Hive, Spark, Airflow).
- Streaming technologies experience (Kafka or Kinesis).
- Practical Databricks capabilities (Unity Catalog, Delta Lake, MLflow) and solid MLOps practices (CI/CD, model registry, monitoring).
- Cloud experience across AWS/Azure/GCP, with strong AWS exposure preferred.
- Robust automated testing for data pipelines (unit/integration).
- Strong knowledge of privacy, regulatory, and audit frameworks (GDPR, CCPA, COPPA, SOX).
- Experience in regulated/high-compliance industries (Gaming, Finance, Healthcare).
- Excellent stakeholder management, problem-solving, and cross-functional communication with the ability to influence without authority.
What you will do
Technology, Architecture & Platforms
- Evolve our lakehouse/analytics reference architecture across AWS, Snowflake, and Databricks (Delta Lake, Unity Catalog) for scale, cost, and reliability.
- Standardize Databricks workspaces—cluster policies, repos/CI/CD, secrets, cost guardrails, and operational SLAs.
- Implement MLOps with MLflow, a feature store, versioned data/code, automated CI/CD, and model promotion/rollback across environments.
- Enforce security-by-default—IAM/SSO, RBAC, encryption, tokenization, and PII protection across platforms.
- Build reliable ingestion, transformation, and services (Python/Flask, Spark, Airflow/Databricks Jobs) with tests, observability, and SLAs.
- Integrate data/ML platforms with game analytics, CDP, personalization, and real-time streams via Kafka/Kinesis; coach teams on best practices.
Data Trust & Governance
- Establish enterprise policies, standards, ownership/stewardship, and decision forums; drive adoption through enablement and training.
- Define classification, retention, and lifecycle; enforce RBAC and encryption for sensitive player data.
- Operate metadata and catalog (DataHub/Atlan/Informatica) to deliver end‑to‑end lineage, impact analysis, and discoverability.
Align key metrics, definitions, and a central glossary across studios; publish and maintain canonical KPIs.
- Implement data quality rules with profiling, monitoring, and remediation workflows governed by SLAs.
- Ensure GDPR/CCPA/COPPA/SOX compliance; operationalize DSAR/Right‑to‑be‑Forgotten and partner with Legal/Security on audits and risk.
Data Modeling
- Lead conceptual, logical, and physical models for player, gameplay, commerce, and marketing; select Kimball/Inmon/Hybrid as appropriate.
- Deliver performant star schemas, conformed dimensions, SCDs, and data contracts in Snowflake/Databricks; govern naming, versioning, and lineage.
As an equal opportunity employer, we are committed to ensuring that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform their essential job functions, and to receive other benefits and privileges of employment. Please contact us if you need reasonable accommodation.
*Please note that 2K Games and its studios never uses instant messaging apps or personal email accounts to contact prospective employees or conduct interviews and when emailing, only use 2K.com accounts.*
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Навыки
- Snowflake
- Databricks
- Python
- SQL
- AWS
- Apache Spark
- Apache Airflow
- Kafka
- MLflow
- Data Modeling
- Data Governance
- Flask
- Delta Lake
- Unity Catalog
- ETL
Возможные вопросы на собеседовании
Проверка архитектурного мышления и понимания специфики инструментов.
Как бы вы спроектировали гибридную архитектуру Lakehouse, используя Snowflake и Databricks для обеспечения минимальной задержки данных?
Оценка опыта в управлении данными и соблюдении регуляций.
Опишите ваш опыт внедрения процессов автоматизированного удаления данных (Right-to-be-Forgotten) в соответствии с GDPR в крупных распределенных системах.
Проверка навыков моделирования данных.
В каких случаях вы предпочтете архитектуру Data Vault классической схеме «звезда» Кимбалла при проектировании игровых аналитических систем?
Оценка опыта в MLOps.
Как вы организуете жизненный цикл модели с использованием MLflow и Unity Catalog для обеспечения воспроизводимости результатов?
Проверка навыков взаимодействия со стейкхолдерами.
Расскажите о случае, когда вам нужно было внедрить стандарты управления данными в команде, которая сопротивлялась изменениям. Как вы добились успеха?
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