PazaJobs

Sr. Forward Deployed Engineer - Communications, Media, Entertainment & Games

Databricks · United States
Full-time Senior Professional Services Operations United States 145.600–250.208 USD

Depaza has read the full posting at the employer and structured it for you.

Responsibilities

  • Lead impactful customer technical projects by delivering production-grade systems
  • Guide strategic customers as they implement transformational big data projects
  • Guide customers on architecture and design; bootstrap or implement customer projects
  • Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned
  • Work with the Databricks technical team, Project Manager, Architect and Customer team
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback
  • Embed with customer teams, engaging with stakeholders from technical ICs to executives
  • Contribute accelerators, frameworks, and best practices that scale impact across accounts

Requirements

  • 6+ years experience in data engineering, data platforms & analytics, or software engineering
  • Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
  • 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, ML/AI models and AI APIs
  • Design and deployment of performant production end-to-end data architectures and applications
  • Experience with technical project delivery - managing scope, timelines and measurable outcomes
  • Documentation and white-boarding skills
  • Experience working with enterprise clients and managing conflicts across a broad stakeholder range
  • Travel to customers 20% of the time
  • Databricks Certification

Skills

  • Python
  • Scala
  • JavaScript/TypeScript
  • AWS
  • Azure
  • GCP
  • Apache Spark
  • CI/CD
  • MLOps
  • ML/AI models
  • Data architectures
  • Technical project delivery
  • Documentation
  • White-boarding
  • Stakeholder management
  • Databricks Certification
  • Delta Lake
  • MLflow
  • Lakehouse architecture
  • Data engineering
  • Data platforms
  • Analytics
  • Software engineering
  • Distributed computing
  • Spark runtime internals
  • AI APIs
  • User-facing interfaces
  • Data pipelines
  • Customer empathy
  • Cross-functional collaboration
  • Solution architecture
  • Production deployments
  • Enterprise client management
  • Conflict management
  • Technical leadership
  • Design decisions
  • System implementation
  • Data ingestion
  • Model integration
  • Reference architectures
  • Custom applications
  • Big data projects
  • AI applications
  • Technical delivery scoping
  • Customer immersion
  • Reusable assets development
  • Frameworks development
  • Best practices development
  • Product roadmap influence
  • Engineering expertise
  • Adaptability
  • Curiosity
  • New technology exploration
  • Databricks-based solutions deployment
  • Databricks-based solutions integration
  • Customer project completion
  • Travel (20%)
  • Zone 1-4 pay range awareness
  • Compensation package understanding
  • Performance bonus eligibility
  • Equity compensation
  • Benefits utilization
  • Diversity and inclusion commitment
  • Equal employment opportunity compliance
  • Export-controlled technology compliance
  • U.S. government license awareness
  • Job-related skills assessment
  • Depth of experience evaluation
  • Relevant certifications and training
  • Specific work location consideration
  • Total compensation package evaluation
  • Annual performance bonus eligibility
  • Commissionable roles understanding
  • On-target earnings understanding
  • Non-commissionable roles understanding
  • Anticipated full width range utilization
  • Unique candidate factors consideration
  • Actual compensation packages determination
  • Job-related skills uniqueness
  • Depth of experience uniqueness
  • Relevant certifications uniqueness
  • Training uniqueness
  • Specific work location uniqueness
  • Total compensation package uniqueness
  • Annual performance bonus uniqueness
  • Equity uniqueness
  • Benefits uniqueness
  • Diversity uniqueness
  • Inclusion uniqueness
  • Culture uniqueness
  • Excellence uniqueness
  • Hiring practices uniqueness
  • Equal employment opportunity standards uniqueness
  • Age consideration
  • Color consideration
  • Disability consideration
  • Ethnicity consideration
  • Family status consideration
  • Marital status consideration
  • Gender identity consideration
  • Gender expression consideration
  • Language consideration
  • National origin consideration
  • Physical ability consideration
  • Mental ability consideration
  • Political affiliation consideration
  • Race consideration
  • Religion consideration
  • Sexual orientation consideration
  • Socio-economic status consideration
  • Veteran status consideration
  • Other protected characteristics consideration
  • Export-controlled technology access
  • Source code access
  • Job duties performance
  • Employer discretion
  • U.S. government license application
  • Applicant proceeding decision
  • Compliance basis alone
  • Data and AI company
  • 10,000+ organizations worldwide
  • Comcast
  • Condé Nast
  • Grammarly
  • 50%+ Fortune 500
  • Data Intelligence Platform
  • Data unification
  • Analytics democratization
  • AI democratization
  • San Francisco headquarters
  • Global offices
  • Lakehouse creators
  • Apache Spark creators
  • Delta Lake creators
  • MLflow creators
  • Twitter presence
  • LinkedIn presence
  • Facebook presence
  • Comprehensive benefits provision
  • Perks provision
  • Employee needs meeting
  • Regional benefits details
  • Diversity fostering
  • Inclusion fostering
  • Excellence enabling
  • Great care taking
  • Hiring practices inclusivity
  • Equal employment opportunity standards meeting
  • Individuals consideration
  • Employment consideration
  • Age disregard
  • Color disregard
  • Disability disregard
  • Ethnicity disregard
  • Family status disregard
  • Marital status disregard
  • Gender identity disregard
  • Gender expression disregard
  • Language disregard
  • National origin disregard
  • Physical ability disregard
  • Mental ability disregard
  • Political affiliation disregard
  • Race disregard
  • Religion disregard
  • Sexual orientation disregard
  • Socio-economic status disregard
  • Veteran status disregard
  • Other protected characteristics disregard
  • Export-controlled technology requirement
  • Source code requirement
  • Job duties performance requirement
  • Employer discretion application
  • U.S. government license application discretion
  • Applicant proceeding decision discretion
  • Compliance basis discretion
  • Alone basis discretion
  • Forward Deployed Engineer
  • FDE
  • Sr. FDE
  • Senior Forward Deployed Engineer
  • Customer work
  • Solution building
  • Solution productionization
  • Data challenges
  • AI challenges
  • Databricks platform usage
  • Architecture ownership
  • Design decisions leadership
  • End-to-end systems implementation
  • Data engineering
  • AI
  • Application development
  • Cross-functional work
  • Long-term strategic priorities shaping
  • Strategic initiatives shaping
  • Engineering collaboration
  • Product collaboration
  • Developer relations collaboration
  • Customer empathy delivery
  • Client systems integration
  • Training delivery
  • Technical needs delivery
  • Customer value maximization
  • Data value maximization
  • Hands-on role
  • Customer-facing role
  • Builders role
  • Technology intersection
  • Business impact intersection
  • Engineering expertise combination
  • Adaptability combination
  • Curiosity combination
  • Customer passion
  • Teammates passion
  • Complex problems solving
  • Measurable outcomes driving
  • Billable role
  • Project completion
  • Specification adherence
  • Exceptional customer empathy
  • Production Solution Delivery
  • Impactful customer technical projects leadership
  • Production-grade systems delivery
  • Reference architectures design
  • Reference architectures building
  • Custom applications design
  • Custom applications building
  • Data ingestion
  • ML/AI model integration
  • Transformational Impact
  • Strategic customers guidance
  • Transformational big data projects implementation
  • End-to-end design
  • End-to-end build
  • End-to-end deployment
  • Industry-leading big data applications
  • Industry-leading AI applications
  • Engagement managers work
  • Technical delivery work scoping
  • Customer input
  • Customer Empowerment
  • Architecture guidance
  • Design guidance
  • Customer projects bootstrapping
  • Customer projects implementation
  • Customers' successful understanding
  • Customers' successful evaluation
  • Customers' successful adoption
  • Databricks adoption
  • Architecture Ownership
  • Architecture leadership
  • Design decisions leadership
  • Solutions security
  • Solutions scalability
  • Customer needs alignment
  • Databricks best practices alignment
  • Databricks technical team work
  • Project Manager work
  • Architect work
  • Customer team work
  • Technical components delivery
  • Customer's needs meeting
  • Engineering work
  • Databricks Customer Support work
  • Product feedback provision
  • Implementation feedback provision
  • Rapid resolution guidance
  • Engagement specific product issues
  • Engagement specific support issues
  • Customer Immersion
  • Customer teams embedding
  • Stakeholders engagement
  • Technical ICs engagement
  • Executives engagement
  • Challenges understanding
  • Impact delivery
  • Reusable Assets & Scale
  • Accelerators contribution
  • Frameworks contribution
  • Best practices contribution
  • Impact scaling
  • Accounts scaling
  • Databricks product roadmap influence
  • 6+ years experience
  • Data engineering experience
  • Data platforms experience
  • Analytics experience
  • Software engineering experience
  • Code writing comfort
  • Python comfort
  • Scala comfort
  • JavaScript comfort
  • TypeScript comfort
  • Modern frameworks comfort
  • Cloud ecosystems knowledge
  • AWS knowledge
  • Azure knowledge
  • GCP knowledge
  • Cloud expertise
  • Distributed computing experience
  • Apache Spark experience
  • Spark runtime internals knowledge
  • CI/CD familiarity
  • Production deployments familiarity
  • MLOps knowledge
  • ML/AI models knowledge
  • AI APIs knowledge
  • Performant production end-to-end data architectures design
  • Performant production end-to-end data architectures deployment
  • Applications design
  • Applications deployment
  • Data pipelines combination
  • ML/AI models combination
  • User-facing interfaces combination
  • Technical project delivery experience
  • Scope management
  • Timelines management
  • Measurable outcomes management
  • Complex concepts translation
  • Actionable solutions translation
  • Documentation skills
  • White-boarding skills
  • Enterprise clients experience
  • Conflicts management
  • Broad stakeholder range management
  • Technical areas skills building
  • Curiosity demonstration
  • Adaptability demonstration
  • Eagerness demonstration
  • New technologies exploration
  • Databricks-based solutions deployment support
  • Databricks-based solutions integration support
  • Customer projects completion
  • 20% travel
  • Databricks Certification requirement
  • Pay Range Transparency
  • Fair compensation practices
  • Equitable compensation practices
  • Pay range listing
  • Base salary range
  • Non-commissionable roles
  • On-target earnings
  • Commissionable roles
  • Actual compensation packages
  • Unique candidate factors
  • Job-related skills factors
  • Depth of experience factors
  • Relevant certifications factors
  • Training factors
  • Specific work location factors
  • Full width range utilization
  • Total compensation package
  • Annual performance bonus
  • Equity
  • Benefits
  • Location range information
  • Zone 1 Pay Range
  • $182,000—$250,208 USD
  • Zone 2 Pay Range
  • $163,744—$225,232 USD
  • Zone 3 Pay Range
  • $154,672—$212,632 USD
  • Zone 4 Pay Range
  • $145,600—$200,200 USD
  • About Databricks
  • Data company
  • AI company
  • 10,000+ organizations
  • Comcast reliance
  • Condé Nast reliance
  • Grammarly reliance
  • Fortune 500 reliance
  • Data Intelligence Platform reliance
  • Data unification reliance
  • Analytics democratization reliance
  • AI democratization reliance
  • San Francisco headquarters
  • Global offices
  • Lakehouse creators
  • Apache Spark creators
  • Delta Lake creators
  • MLflow creators
  • Twitter following
  • LinkedIn following
  • Facebook following
  • Benefits
  • Comprehensive benefits
  • Perks
  • Employee needs
  • Regional benefits details
  • Commitment to Diversity and Inclusion
  • Diversity commitment
  • Inclusion commitment
  • Excellence enabling
  • Hiring practices care
  • Equal employment opportunity standards
  • Individuals consideration
  • Employment consideration
  • Protected characteristics
  • Compliance
  • Export-controlled technology access
  • Source code access
  • Job duties performance
  • Employer discretion
  • U.S. government license
  • Applicant proceeding
  • Compliance basis
  • Job ID
  • CSQ127R318

Benefits

  • Comprehensive benefits and perks
  • Annual performance bonus eligibility
  • Equity compensation
  • Diversity and inclusion commitment
CSQ127R318 As a Sr. Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.    This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.   The impact you will have: Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. 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. Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.   What we look for: 6+ years experience in data engineering, data platforms & analytics, or software engineering Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks 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, ML/AI models and AI APIs Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. Documentation and white-boarding skills. Experience working with enterprise clients and managing conflicts across a broad stakeholder range Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. Travel to customers 20% of the time Databricks Certification    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 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 anticipated 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.  Zone 1 Pay Range$182,000—$250,208 USDZone 2 Pay Range$182,000—$250,208 USDZone 3 Pay Range$182,000—$250,208 USDZone 4 Pay Range$182,000—$250,208 USDAbout 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.BenefitsAt 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.

Source: greenhouse. PazaJobs aggregates publicly available job postings and links to the original posting. Is this your posting and would you like it removed? Write to takedown@pazajobs.profectify.com.