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Solutions Architect - Digital Native Business

Databricks Inc.

United States

Remote

USD 139,000 - 248,000

Full time

30+ days ago

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Job summary

An innovative firm is seeking a Solutions Architect to join their Digital Natives team. In this role, you will collaborate with top-tier data engineering and data science teams, shaping the future of big data. You will provide technical leadership, guiding customers through best practices and developing solutions using advanced platforms and APIs. This position offers the chance to work on strategic projects involving data engineering, machine learning, and SQL workflows, while also promoting open-source contributions. If you're passionate about data and eager to make an impact, this role is perfect for you.

Benefits

Annual performance bonus
Equity options
Comprehensive health benefits
Flexible work hours
Remote work opportunities

Qualifications

  • 5+ years in data engineering, data science, or technical architecture roles.
  • Comfortable programming and debugging in Python and SQL.

Responsibilities

  • Partner with sales to provide technical leadership and solutions.
  • Consult on Big Data architectures and implement proof of concepts.

Skills

Data Engineering
Data Science
Technical Architecture
Python
SQL
Machine Learning
Big Data Technologies

Education

Bachelor's Degree in Computer Science or related field

Tools

AWS
Azure
GCP
Apache Spark
Delta Lake
MLflow

Job description

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

As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide 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.
  • 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.
  • 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 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.

Local Pay Range: $139,700 — $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 Twitter, LinkedIn, 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 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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