Resident Solutions Architect - Data Engineering (Financial Services)

Posted 11 Days Ago
Be an Early Applicant
Hiring Remotely in United States
Remote
125K-221K Annually
Senior level
Big Data • Software
The Role
As a Resident Solutions Architect, you will assist clients in tackling their big data challenges using the Databricks platform, managing projects that involve architecture design, deployment, and integration of data solutions. You will work closely with engagement managers and engineering teams to ensure successful delivery of services, providing support and fostering customer relationships.
Summary Generated by Built In

CSQ325R22

This position can be remote.

As a Resident Solutions Architect (RSA) on our Professional Services team, you will work with customers on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

  • Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
  • Work with engagement managers to scope variety of  professional services work with input from the customer
  • Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
  • Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  • Provide an escalated level of support for customer operational issues
  • Collaborate with the Databricks Technical, Project Manager, Architect and Customer teams to ensure the technical components of the engagement are delivered to meet customer's needs
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues

What we look for:

  • 6+ years experience in data engineering, data platforms & analytics
  • Comfortable writing code in either Python or Scala
  • Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
  • Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
  • Familiarity with CI/CD for production deployments
  • Working knowledge of MLOps
  • Design and deployment of performant end-to-end data architectures
  • Experience with technical project delivery - managing scope and timelines
  • Documentation and white-boarding skills
  • Experience working with clients and managing conflicts
  • Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects
  • Ability to 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

$124,800$220,800 USD

Zone 2 Pay Range

$124,800$220,800 USD

Zone 3 Pay Range

$124,800$220,800 USD

Zone 4 Pay Range

$124,800$220,800 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 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.

Top Skills

Python
Scala
The Company
Seattle, WA
0 Employees
Hybrid Workplace
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.

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