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Specialist Solutions Architect - Data Intelligence Platform

As a Specialist Solutions Architect (SSA) - Data Intelligence Platform, you will guide partners in building big data solutions on Databricks that span a large variety of use cases. You will be in a partner-facing role, working with and supporting our field Solution Architects and partner teams, that requires hands-on production experience with SQL, Apache Spark™ and expertise in other data technologies.  SSAs help partners build capabilities for design and successful implementation of essential workloads while aligning their technical roadmap for expanding the usage of the Databricks Intelligence Platform. As a deep go-to-expert reporting to the Field Engineering Leadership, 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 data governance, data science, machine learning, streaming, performance tuning, industry expertise, or more.

The impact you will have:

  • Provide technical leadership to guide strategic partners to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
  • Architect production level data pipelines, including end-to-end pipeline load performance testing and optimization
  • Become a technical expert in an area such as data lake technology, big data streaming, or big data ingestion and workflows
  • Assist Solution Architects with aspects of the technical sale as they work alongside partners including customizing proof of concept content, estimating workload sizing, and custom architectures
  • Provide tutorials and training to improve partner community adoption (including hackathons and conference presentations)
  • Contribute to the Databricks Community

What we look for:

    • 5+ years experience in a technical role with expertise in at least one of 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, partner life-time value.
      • Data Science or Machine Learning Ops: Design and build of production infrastructure, model management, and deployment of advanced analytics that drives measurable business value (ie. getting models running in production).
    • Must be able to work collaboratively and independently to achieve outcomes supporting go-to-market priorities and have the interpersonal savvy to influence both partners and internal stakeholders without direct authority
    • Deep Specialty Expertise in at least one of the following areas:
      • Expertise in data governance systems and solutions that may span technologies such as Unity Catalog, Alation, Collibra, Purview, etc.
      • Experience with high-performance, production data processing systems (batch and streaming) on distributed infrastructure.
      • Experience building large-scale real-time stream processing systems; expertise in high-volume, high-velocity data ingestion, change data capture, data replication, and data integration technologies.
      • Experience migrating and modernizing Hadoop jobs to public cloud data lake platforms, including data lake modeling and cost optimization.
      • Expertise in cloud data formats like Delta and declarative ETL frameworks like DLT.
      • Expertise in building GenAI solutions such as RAG, Finetuning, or Pre-training for custom model creation.
    • Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience.
    • Maintain and extend production data systems to evolve with complex needs.
    • Production programming experience in SQL and Python, Scala, or Java.
    • Experience with the AWS, Azure, or GCP clouds.
    • 3+ years professional experience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and architectures
    • 3+ years with system integration partner or customer-facing experience in a pre-sales or post-sales role (consultant working for a partner)
    • 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 will 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 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
$161,300$247,300 USD
Zone 2 Pay Range
$161,300$247,300 USD
Zone 3 Pay Range
$161,300$247,300 USD
Zone 4 Pay Range
$161,300$247,300 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

$204300 / YEARLY (est.)
min
max
$161300K
$247300K

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 Specialist Solutions Architect - Data Intelligence Platform, Databricks

Are you passionate about big data and ready to take on an exciting challenge? Join Databricks as a Specialist Solutions Architect - Data Intelligence Platform and be at the forefront of innovation! In this partner-facing role, you’ll guide our partners in building cutting-edge big data solutions on Databricks, utilizing technologies like SQL and Apache Spark. Collaborate with Solution Architects and partner teams to tailor data solutions that enhance partner capabilities and align with their technical roadmaps. You’ll have the opportunity to build production-level data pipelines, conduct load performance testing, and dive deep into areas such as data governance and machine learning. At Databricks, we prioritize your growth, offering mentorship and continuous learning opportunities so you can become a recognized expert in your field. We're looking for someone with 5+ years of experience in a technical role, who enjoys both collaborative and independent work, and has a strong background in data technologies. Whether you’re architecting solutions, training partners at conferences, or contributing to the Databricks Community, your impact will resonate far and wide. This is an opportunity to truly shape the future of data intelligence while being supported by a diverse and inclusive culture. Plus, with the option to work remotely and flexible travel requirements, you can enjoy a work-life balance that fits your lifestyle. Become part of our mission to unify and democratize data, analytics, and AI today!

Frequently Asked Questions (FAQs) for Specialist Solutions Architect - Data Intelligence Platform Role at Databricks
What are the responsibilities of a Specialist Solutions Architect - Data Intelligence Platform at Databricks?

In the Specialist Solutions Architect - Data Intelligence Platform role at Databricks, you will guide partners in constructing big data solutions, focusing on key responsibilities like providing technical leadership, architecting production-level data pipelines, and assisting Solution Architects with technical sales. Your work will encompass a variety of projects, from architectural design to model deployment, while you also conduct trainings to foster partner community adoption.

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What qualifications are needed to become a Specialist Solutions Architect - Data Intelligence Platform at Databricks?

To qualify for the Specialist Solutions Architect - Data Intelligence Platform position at Databricks, you should possess at least 5 years of experience in a technical role. A Bachelor's degree in Computer Science or a related field is preferred. Candidates should have expertise in software engineering, data applications engineering, or data science, as well as familiarity with big data technologies such as Spark and Hadoop.

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How does Databricks support career growth for Specialist Solutions Architects?

Databricks is committed to the growth of its Specialist Solutions Architects by offering various mentorship programs, training sessions, and opportunities to specialize in different areas such as data governance or machine learning. You'll enhance your skills while contributing to innovative projects and leading training sessions that enrich the wider community.

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What is the importance of hands-on experience for the Specialist Solutions Architect role at Databricks?

Hands-on experience is crucial for the Specialist Solutions Architect role at Databricks, as it ensures candidates can effectively guide partners through implementing robust data solutions. Familiarity with tools like SQL, Spark, and cloud infrastructures equips you with the expertise needed to architect successful data pipelines and troubleshoot complex issues.

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What does a typical day look like for a Specialist Solutions Architect - Data Intelligence Platform at Databricks?

A typical day for a Specialist Solutions Architect at Databricks involves collaborating with partners to understand their data needs, designing tailored big data solutions, and facilitating technical training sessions. You may also engage in performance testing of data pipelines, participate in internal strategy meetings, and contribute to community initiatives to share knowledge and drive data adoption.

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Common Interview Questions for Specialist Solutions Architect - Data Intelligence Platform
What strategies do you use to manage large datasets effectively?

When addressing large datasets, I focus on optimizing data pipelines using Apache Spark's parallel processing capabilities and utilizing techniques such as partitioning. Ensuring efficient schema design and implementing data governance practices also helps maintain data quality and accessibility.

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Can you explain your experience with streaming technologies like Spark Streaming?

I have extensive experience with Spark Streaming, where I developed real-time data processing applications to handle continuous data streams. My approach involves setting up robust ingestion frameworks and leveraging window operations to manage stateful computations while ensuring scalability and performance.

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How do you approach designing a proof of concept for a new client?

To design an effective proof of concept, I start by understanding the client's specific requirements and objectives. I then tailor a solution that demonstrates the capabilities of the Databricks platform, ensuring that the prototype addresses their pain points while showcasing scalability and performance.

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What techniques have you implemented for performance tuning in data pipelines?

In my experience, I employ a variety of performance tuning techniques, including optimizing Spark configurations, using caching strategies for frequently accessed data, and adjusting data partitioning to enhance parallelism. Monitoring and profiling tools also play a key role in identifying bottlenecks for resolution.

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Describe a successful project you've led involving data governance.

I led a project centered on implementing a data governance framework using Unity Catalog. By aligning stakeholders and establishing clear data policies, I successfully enhanced data quality and accessibility, ultimately driving efficiency across several business units while ensuring compliance with regulations.

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How do you keep up with the latest trends in big data and cloud technologies?

I stay up-to-date with the latest trends by participating in webinars, attending industry conferences, and following thought leaders on platforms like LinkedIn. Engaging with the developer community through forums and contributing to open-source projects allows me to gain insights into emerging technologies and best practices.

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What role does communication play in your work as a Specialist Solutions Architect?

Effective communication is vital in my role as a Specialist Solutions Architect. It allows me to translate complex technical concepts into digestible information for partners and stakeholders, ensuring alignment and understanding across teams while fostering collaboration toward common goals.

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How do you prioritize tasks when managing multiple projects?

I prioritize tasks by analyzing deadlines, project impact, and resource availability. Utilizing project management tools also helps me track progress, set milestones, and ensure that critical tasks are addressed promptly while maintaining flexibility to adapt to changing priorities.

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What have you learned from your experiences working with clients?

Working with clients has taught me the importance of building trust and actively listening to their needs. Tailoring solutions to their specific challenges not only strengthens relationships but also leads to better outcomes and increased satisfaction with the services provided.

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Can you describe your experience with cloud services such as AWS or Azure?

I have hands-on experience with cloud platforms like AWS and Azure, where I've deployed data solutions leveraging their respective technologies. My proficiency with services such as S3, Redshift, and Azure Data Lake has enabled me to create scalable architectures that optimize performance and cost efficiency.

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

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DATE POSTED
March 2, 2025

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