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CSQ427R96
As a Sr. Forward Deployed Engineer in our Professional Services team you will work with clients 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. FDEs are billable and know how to complete projects according to specification with excellent customer service. You will report to the Sr. Manager, Professional Services.
The impact you will have:
- You will work on a variety of impactful customer technical projects which may include building reference architectures, how-to's and production grade MVPs / Greenfield projects
- 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 strategic customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks
- Provide an escalated level of support for customer operational issues.
- You will work with the Databricks technical team, Project Manager, Architect and Customer team 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:
- 8+ years experience with Big Data Technologies such as Apache Spark™, Kafka, Cloud Native and Data Lakes in a customer-facing post-sales, technical architecture or consulting role.
- Comfortable writing code in either Python or Scala.
- 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.
- Travel to customers 20 - 30% of the time
- Nice to have: Databricks Certification
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
- 8+ years of experience with big data technologies such as Apache Spark, Kafka, cloud-native technologies, and data lakes in a customer-facing post-sales, technical architecture, or consulting role
- Ability to write code in Python or Scala
- Experience delivering technical projects, including managing scope and timelines
- Strong documentation and whiteboarding skills
- Experience working with clients and managing conflicts
- Technical skills supporting deployment and integration of Databricks-based solutions
- Ability to travel to customers 20–30% of the time
- 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.
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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.
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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.
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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
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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