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SeniorУдалённоПолная занятость

Sr. Specialist Solutions Engineer - Data Warehousing (Financial Services)

Оценка ИИ

Отличная позиция в компании-лидере рынка с высокой компенсацией и возможностью работать с передовыми технологиями (Spark, Delta Lake). Роль предлагает хороший баланс между глубокой технической экспертизой и стратегическим влиянием на бизнес клиентов.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью глубоких экспертных знаний в архитектуре Lakehouse и MPP-системах, а также опытом работы с клиентами. Требуется не только техническая грамотность в SQL/Python, но и навыки предпродажной подготовки и миграции данных.

Анализ зарплаты

Медиана185 000 $
Рынок160 000 $ – 220 000 $
Оценка ИИ

Предлагаемый диапазон $152k–$209k полностью соответствует рыночным стандартам для Senior Solutions Engineer в США, особенно в специализированных нишах вроде Data Warehousing. Верхняя граница диапазона даже несколько превышает медиану, что характерно для топовых технологических компаний уровня Databricks.

Сопроводительное письмо

I am writing to express my strong interest in the Sr. Specialist Solutions Engineer position at Databricks. With over [Number] years of experience in data warehousing and a deep focus on lakehouse architecture, I have successfully led numerous cloud transformations and performance tuning initiatives for large-scale analytical workloads. My background in optimizing SQL performance and migrating legacy EDW systems to the cloud aligns perfectly with the mission of your Specialist Field Engineering team.

Throughout my career, I have developed a keen ability to bridge the gap between complex technical requirements and business outcomes. I am particularly drawn to Databricks because of its pioneering role in the Data Intelligence Platform space. I am confident that my hands-on expertise in Python, SQL, and cloud ecosystems (AWS/Azure/GCP), combined with my experience in customer-facing pre-sales roles, will allow me to drive significant value for your financial services clients and contribute to the Databricks community.

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Описание вакансии

FEQ227R150

Mission

As a Sr. Specialist Solutions Engineer (SSA) - Data Warehousing, you will guide customers in their cloud data warehousing transformation with Databricks that span a large variety of use cases.  You will be in a customer-facing role, working with and supporting Solution Architects, that requires hands-on production experience with large scale data warehousing technologies and lake house architecture.  SSAs help customers through evaluations and successful production planning for their business intelligence workloads while aligning their technical roadmap for the Databricks Data Intelligence Platform.  As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs and establish yourself in the data warehousing specialty - including performance tuning, data modeling, winning competitive evaluations, architecture design, and production migration planning.

The impact you will have:

  • Provide technical leadership to guide strategic customers to successful cloud transformations on large scale data warehousing workloads - ranging from evaluation to architecture design to production deployment.
  • Prove the value of the Databricks Intelligence Platform for customer workloads by architecting production workloads, including end-to-end pipeline load performance testing and optimization.
  • Become a technical expert in an area such as competitive data warehousing evaluations or helping set up successful workload migrations.
  • Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing and performance, and tuning workloads for production.
  • Provide tutorials and training to improve community adoption (including hackathons and conference presentations)
  • Contribute to the Databricks Community.

What we look for:

  • 3+ years of experience in a technical role with expertise in data warehousing - such as query tuning, performance tuning, troubleshooting, data governance, debugging MPP data warehouses or other big data solutions, or migration workloads from EDW systems.
  • Experience with design and implementation of data warehousing technologies including relational databases, SQL, data analytics, NoSQL, MPP, OLTP, and OLAP.
  • Deep Specialty Expertise in at least one of the following areas:
  • Experience scaling large analytical data workloads in the cloud that are performant and cost-effective.
  • Maintained, extended, or migrated a production data warehouse system to evolve with complex needs, including data modeling, data governance needs, and integration with business intelligence tools.
  • Experience successfully migrating on-premise EDW workloads to the public cloud.
  • Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience.
  • Production programming experience in SQL and Python, Scala, or Java.
  • Experience with the AWS, Azure, or GCP clouds is highly desirable.
  • 3 years of professional experience with data warehousing and big data technologies (Ex: SQL, Redshift, SAP, Synapse, EMR, OLAP & OLTP workloads)
  • 3 years of customer-facing experience in a pre-sales or post-sales role
  • Can meet expectations for technical training and role-specific outcomes within 6 months of hire
  • This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$152,300—$209,450 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on TwitterLinkedIn and Facebook.

BenefitsAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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Навыки

  • AWS
  • Azure
  • Python
  • SQL
  • Google Cloud Platform
  • Delta Lake
  • Apache Spark
  • Java
  • Business Intelligence
  • ETL
  • NoSQL
  • Data Warehousing
  • Scala
  • OLAP

Возможные вопросы на собеседовании

Проверка понимания ключевой концепции Databricks и умения объяснить её преимущества перед традиционными хранилищами.

Как бы вы объяснили преимущества архитектуры Lakehouse по сравнению с традиционным хранилищем данных (EDW) техническому директору финансовой компании?

Оценка практического опыта в оптимизации производительности, что является критической частью роли.

Опишите ваш процесс выявления и устранения узких мест в производительности сложного SQL-запроса в распределенной среде.

Проверка навыков работы с облачными провайдерами и понимания специфики облачной инфраструктуры.

С какими основными проблемами вы сталкивались при миграции on-premise данных в облако (AWS/Azure/GCP) и как вы их решали?

Оценка способности работать в пре-сейлс и убеждать клиентов в ценности решения.

Расскажите о случае, когда вам пришлось проводить Proof of Concept (PoC) для скептически настроенного клиента. Как вы доказали ценность платформы?

Проверка знаний в области управления данными, что критично для финансового сектора.

Каков ваш опыт в реализации стратегий управления данными (Data Governance) и обеспечения безопасности в больших аналитических системах?

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databricks
Страна
США
Зарплата
152 300 $ – 209 450 $