CSQ426R258
As a Staff Forward Deployment Engineer (DE/AI Spike), you will be part of the Professional Services team and work with clients on short to medium term customer engagements solving their big data problems using Apache Spark™ and the Databricks Data Intelligence Platform. You will be in a customer-facing role that requires deep hands-on expertise in Apache Spark™ and data engineering, along with a variety of knowledge of the big data ecosystem. You will guide our largest customers, implementing pipelines from data engineering through model building and deployment, plus other technical tasks to help customers to get value out of their data with Databricks. You will report to the Director, Professional Services.
The impact you will have:
- You will guide customers as they implement transformational big data projects, including end-to-end development and deployment of industry-leading big data and AI applications
- You will assure that Databricks best practices are being used within all projects and that our quality of service and implementation is strictly followed
- You will facilitate technical workshops, discovery and design sessions, customer requirements gathering and scoping for new and existing strategic customers
- Assist the Professional Services leader and project managers with level of effort estimation and mitigation of risk within customer proposals and statements of work
- Architect, design, develop, deploy, operationalize and document complex customer engagements individually or as part of an extended team as the technical lead and overall authority
- Knowledge transfer, enablement and mentoring of other team members, customers and partners, including developing reusable project artifacts
- Provide experience to the consulting team, provide best practices in client engagement to other teams
What we look for:
- 10+ years of experience in Design and Implementation of Big Data technologies (Apache Spark™) and familiarity with data architecture patterns (data warehouse, data lake, streaming, Lambda/Kappa architecture)
- Deep technical knowledge and comfortable coding in Python or Scala
- Familiarity with GCP/Azure/AWS/EC2 cloud deployment models (Public vs. VPC) is a plus
- Experience working with teams across a diverse geographic area
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 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
- 10+ years of experience in Design and Implementation of Big Data technologies (Apache Spark)
- Deep technical knowledge and comfortable coding in Python or Scala
- Familiarity with GCP/Azure/AWS/EC2 cloud deployment models
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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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
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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