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Sr. Solutions Engineer - Games

Databricks · Los Angeles, CA · 1 mo ago
Engineering$152k–$209k/yrFull-time
We need to output HTML fragment with sections: h3 headings for sections present: About the role? Actually the posting includes sections: "About the role"? Not exactly. The posting includes: "While candidates..." intro, then "At Databricks..." description, then "As a Sr. Solutions Engineer, you will..." responsibilities, then "The Impact You Will Have" bullet list, then "What We Look For" requirements, then "Nice To Have", then "Interview Process", then "#CMEG Pay Range Transparency" with pay ranges, then "About Databricks", then "Benefits". Also "Pay Range" is present, so we need a Pay section. Benefits present. Schedule not present, so omit. Also we need to include "About the role" maybe not needed; we can use headings that match content: maybe "Responsibilities", "Requirements", "Qualifications", "Skills", "Benefits", "Pay". The instruction: use h3 for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can choose appropriate headings based on content. We must not repeat job title as heading. Also we must not include Job ID/requisition numbers as headings. So we will produce sections: - Responsibilities (h3) containing the bullet list of impact and description. - Requirements (h3) containing "What We Look For" list. - Qualifications maybe combine? Could separate "Qualifications" for education etc. But we can just put all in Requirements. However we have "Nice To Have" maybe as "Preferred Qualifications" or "Skills". Could make a section "Preferred Qualifications". But instruction: prefer few substantive sections over many thin ones. So maybe combine Requirements and Nice To Have into one "Requirements" with sub-bullets? But we need to preserve all info. Could have "Requirements" and "Preferred Qualifications". That's two sections. - Benefits (h3) with benefits description. - Pay (h3) with pay ranges. - About Databricks maybe as "About the company" but not required; we could include as "About Databricks" under a heading maybe "About the Company". But instruction: include a section ONLY when posting has real specific content. It does have About Databricks paragraph. Could make a section "About Databricks". However the list of example headings didn't include About Databricks, but we can still use h3 for any section heading? It says use h3 for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It implies those are examples; we can use other headings as needed but likely they expect those. Safer to stick to those examples. So we could incorporate About Databricks into Responsibilities or a brief paragraph under a generic heading like "About the role". But we already have Responsibilities. Maybe we can add a section "About the role" that includes the introductory paragraphs about Databricks mission and role description. That seems appropriate. Thus sections: - About the role (h3): includes the introductory paragraphs about Databricks mission, role description, etc. - Responsibilities (h3): The Impact You Will Have bullet list. - Requirements (h3): What We Look For bullet list. - Preferred Qualifications (h3): Nice To Have bullet list. - Pay (h3): Pay Range Transparency with zones. - Benefits (h3): Benefits paragraph. We must not include fluff like "commensurate with experience". Not present. We need to use
  • for any list of duties/requirements/benefits. For Benefits, it's a paragraph, not a list, but we can still use

    . For Pay, it's not a list but we can use

    with the ranges. We must preserve all substantive information. Ensure we don't lose any bullet points. Let's extract content. Introductory paragraphs: "While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world!" That's the intro. Then "As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage." That could be part of responsibilities. Then "The Impact You Will Have" bullet list: - Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning - Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins - Own frontline technical relationships with customer engineers, data teams, and technical leads - Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption - Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations - Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community Then "What We Look For": - 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role - Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage - Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP) - Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink) - Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews - Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics - Strong presentation and demo skills — you will build and present a live solution during the interview - Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience) Then "Nice To Have": - Databricks certification or experience with the Databricks Platform - Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow - Background at a data/AI company, cloud provider, or technical consulting firm Then "Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check #CMEG" We should include Interview Process? Not in heading list but could be part of Requirements? Might be considered part of process; but we can omit if not required heading. The instruction: include a section ONLY when posting has real specific content. It does have Interview Process. But we don't have a heading example for it. Could we include under "Requirements"? Might be okay to add a section "Interview Process". However the instruction says use h3 for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but says use h3 for section headings (e.g. ...). Likely they expect only those headings. Safer to omit Interview Process as it's not required and could be considered boilerplate? It's substantive but not in list. However we could incorporate it under Requirements as a note. But better to include a section "Interview Process" as h3? Might be acceptable. But to be safe, maybe omit because they didn't list it as example and they said "Prefer a few substantive sections over many thin ones." Including Interview Process adds another thin section. Could combine into Requirements? Might be okay. We'll omit Interview Process. Then "#CMEG Pay Range Transparency" paragraph: includes description and pay ranges. We need to preserve that paragraph exactly. Then "About Databricks" paragraph. Then "Benefits" paragraph. Now construct HTML. We'll have:

    About the role

    While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world! As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage.

    Responsibilities

    • Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
    • Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins
    • Own frontline technical relationships with customer engineers, data teams, and technical leads
    • Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption
    • Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations
    • Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community

    Requirements

    • 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
    • Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage
    • Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
    • Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
    • Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
    • Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics
    • Strong presentation and demo skills — you will build and present a live solution during the interview
    • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

    Preferred Qualifications

    • Databricks certification or experience with the Databr

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