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Sr. Specialist Solutions Architect - Data Engineering

FEQ425R614

This role can be remote. 

As a Sr. Specialist Solutions Architect (SSA) - Data Engineering, you will guide customers in building big data solutions on 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 Apache Spark™ and expertise in other data technologies.  SSAs help customers through design and successful implementation of essential workloads while aligning their technical roadmap for expanding the usage of 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 an area of specialty - whether that be streaming, performance tuning, industry expertise, or more.

The impact you will have:

  • Build production ready architectures using novel patterns and leveraging non-standard components to address customer requirements
  • Serve as the trusted technical advisor to technical leads and executives
  • Handle longer-term, complex engagements and/or a variety of short-term requests for assistance
  • Originate and drive initiatives to improve efficiency beyond an immediate team 
  • Drive projects and initiatives with non-linear impact such as creating customer facing collateral (e.g., demos, blog articles, architectures, webinars), 10X or labs projects
  • Contribute to the Databricks Community

What we look for:

  • 7+ years experience in a technical role with expertise in the following:
    • Software Engineering/Data Engineering: data ingestion, streaming technologies - such as Spark Streaming and Kafka, performance tuning, troubleshooting, and debugging Spark or other big data solutions
    • Data Applications Engineering: Build use cases that use data - such as risk modeling, fraud detection, customer life-time value
  • Extensive experience building big data pipelines
  • Experience maintaining and extending production data systems to evolve with complex needs
  • Deep Specialty Expertise in the following areas:
    • Experience scaling big data workloads (such as ETL) that are performant and cost-effective
    • Experience migrating Hadoop workloads to the public cloud - AWS, Azure, or GCP
    • Experience with large scale data ingestion pipelines and data migrations - including CDC and streaming ingestion pipelines
    • Expert with cloud data lake technologies - such as Delta and Delta Live
  • 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
  • 5+ years professional experience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and architectures
  • 5+ 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
  • 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 base 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 utilizes 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.

 

Zone 1 Pay Range
$169,000$299,000 USD
Zone 2 Pay Range
$169,000$299,000 USD
Zone 3 Pay Range
$169,000$299,000 USD
Zone 4 Pay Range
$169,000$299,000 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.

Benefits

At 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.

Average salary estimate

$234000 / YEARLY (est.)
min
max
$169000K
$299000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Sr. Specialist Solutions Architect - Data Engineering, Databricks

Join the exciting world of data engineering with Databricks as a Sr. Specialist Solutions Architect! In this stimulating remote role, you'll be pivotal in guiding customers to build dynamic big data solutions using the award-winning Databricks platform. If you have extensive experience in Apache Spark™ and various data technologies, this is your chance to shine. You'll work closely with Solution Architects and be deeply involved in the design and implementation of critical workloads, aligning customer needs with their technical roadmap. This role not only offers the opportunity to engage directly with clients but also allows you to enhance your own skills through mentorship and training. Your journey will include developing innovative architectures to solve unique customer challenges while serving as a trusted advisor to technical leaders and stakeholders. If you have a knack for driving impactful initiatives, creating customer-facing content, and contributing to community knowledge, you will thrive in this position. With a strong focus on customer success and the ambition to explore your specialty, whether that's streaming, performance optimization, or scaling big data workloads, Databricks presents an environment ripe for growth and innovation. So if you're ready to make a significant impact in the data engineering landscape, Databricks is where you want to be!

Frequently Asked Questions (FAQs) for Sr. Specialist Solutions Architect - Data Engineering Role at Databricks
What does a Sr. Specialist Solutions Architect do at Databricks?

A Sr. Specialist Solutions Architect at Databricks plays a crucial role in helping clients develop and implement big data solutions across various use cases. This role involves hands-on experience with Apache Spark™ and guiding customers through their technical roadmap to leverage the Databricks Data Intelligence Platform effectively.

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What qualifications are needed for the Sr. Specialist Solutions Architect position at Databricks?

Candidates for the Sr. Specialist Solutions Architect position at Databricks should have over 7 years of technical experience in data engineering, strong proficiency in Apache Spark™, and a background in software development. A bachelor’s degree in Computer Science or related fields is typically required.

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What are the main responsibilities of a Sr. Specialist Solutions Architect at Databricks?

Main responsibilities include facilitating the design and implementation of data solutions, acting as a technical advisor to clients, creating impactful customer-facing content, and driving both short and long-term project initiatives to improve efficiency and client satisfaction within the Databricks ecosystem.

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How does Databricks support professional growth for Sr. Specialist Solutions Architects?

Databricks promotes professional growth through mentorship, ongoing training programs, and opportunities to specialize in specific areas such as streaming or performance tuning. Team members are encouraged to expand their technical skills and contribute to the Databricks community.

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What kind of projects will a Sr. Specialist Solutions Architect work on at Databricks?

A Sr. Specialist Solutions Architect at Databricks will work on diverse projects, including developing big data pipelines, migrating workloads to the cloud, and creating innovative architectures that meet client demands, such as risk modeling and fraud detection.

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Is the Sr. Specialist Solutions Architect position at Databricks remote?

Yes, the Sr. Specialist Solutions Architect position is remote, allowing a flexible working environment while engaging with clients and team members to deliver extraordinary data engineering solutions.

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What impact do Sr. Specialist Solutions Architects have on the Databricks community?

Sr. Specialist Solutions Architects greatly influence the Databricks community by sharing knowledge through webinars, blog articles, and customer-facing demos. They help shape best practices and drive the adoption of innovative solutions in big data engineering.

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Common Interview Questions for Sr. Specialist Solutions Architect - Data Engineering
Can you explain your experience with Apache Spark™?

When discussing your experience with Apache Spark™, focus on specific projects where you leveraged Spark for data processing, including your role in designing the architecture, performance tuning, and any challenges you overcame during implementation.

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How do you approach building big data pipelines?

To answer this question, describe your workflow for building big data pipelines, including your strategies for data ingestion, transformation, and loading. Emphasize your experience with tools like Kafka and your insights on ensuring scalability and efficiency.

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What strategies do you utilize for performance tuning in big data applications?

Discuss specific performance tuning techniques you have applied, such as optimizing Spark configurations, improving data partitioning, and caching strategies. Offer real-world examples that highlight your results in improving application performance.

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How do you ensure effective collaboration with clients and technical leads?

Explain your approach to client collaboration, including establishing clear communication channels, understanding their requirements deeply, and providing ongoing support to ensure alignment between technical teams and client objectives.

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Describe a challenging data engineering project you have managed.

When discussing a challenging project, outline the complexities involved, your specific responsibilities, the technologies utilized, and how you addressed and resolved those challenges effectively. Conclude with the outcome and learning points.

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What experience do you have with cloud data lake technologies?

Talk about your experience with cloud data lake technologies such as Delta Lake. Provide examples of how you implemented these technologies in projects and the benefits they brought to data management and analytics.

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Can you explain your familiarity with data migration strategies?

Detail your experience with data migration strategies, particularly focusing on migrating Hadoop workloads to cloud environments. Discuss your planning process, tools used, and considerations for ensuring a smooth transition.

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How do you stay updated with industry trends in data engineering?

Discuss your methods for staying informed about industry trends, such as participating in forums, attending conferences, or contributing to open-source projects. Highlight how ongoing learning informs your work and benefits your team.

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What are the key factors for scaling big data workloads effectively?

Elaborate on the factors that are crucial for scaling big data workloads, including architecture design, resource allocation, monitoring, and data processing strategies. Provide examples of successful scaling scenarios you have worked on.

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Describe how you would handle a conflict with a client regarding project scope.

Explain your approach to handling conflicts, focusing on effective communication, active listening to understand the client's perspective, and balancing their needs with project capabilities to find an amicable solution.

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Databricks, the data and AI company, helps data teams solve the world’s toughest problems.

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Full-time, remote
DATE POSTED
November 26, 2024

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