Solutions Architect - Strategic High Tech

Posted 24 Days Ago
Be an Early Applicant
Hiring Remotely in San Francisco, CA, USA
In-Office or Remote
180K-248K Annually
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Develops data and AI architectures for strategic customers, leads technical pre-sales engagements, builds proofs of concept, validates cloud and third-party integrations, and advises on data engineering, data science, machine learning, and SQL workflows. The role also promotes Databricks technologies and open-source projects while partnering with sales, product, engineering, and customer teams.
Summary Generated by Built In

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE

As a Strategic Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape of one of the largest global tech companies by working with the most sophisticated data engineering and data science teams.

Reporting to the Field Engineering Manager, you will collaborate with customer stakeholders, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide one of our largest AI native customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

  • You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
  • Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
  • Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
  • Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

  • 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
  • Experience building distributed data systems
  • Comfortable programming in, and debugging, Python and SQL
  • Have built solutions with public cloud providers such as AWS, Azure, or GCP
  • Expertise in one of the following:
    • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
    • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
  • Available to travel to customers in your region
  • [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
  • Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.


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
$180,000$247,500 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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 click here.

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.

Skills Required

  • 5+ years of experience in data engineering, data science, technical architecture, or a similar pre-sales or consulting role
  • Experience building distributed data systems
  • Programming and debugging experience with Python and SQL
  • Experience building solutions with AWS, Azure, or GCP
  • Expertise in data engineering technologies such as Spark, Hadoop, or Kafka, or data science and machine learning technologies such as pandas, scikit-learn, PyTorch, or TensorFlow
  • Availability to travel to customers in the assigned region
  • Degree in a quantitative discipline such as Computer Science, Applied Mathematics, or Operations Research
  • Databricks Certification

Databricks Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.

  • Healthcare Strength Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
  • Parental & Family Support Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
  • Wellbeing & Lifestyle Benefits Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.

Databricks Insights

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The Company
HQ: San Francisco, CA
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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