Sr. Solutions Engineer - Games

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must only include sections that have real specific content. Remove boilerplate, navigation, EEO, etc. Also remove Job ID etc. Must preserve all substantive info. We need to parse the posting. Let's extract sections: - About the role: The initial paragraph(s) describing mission, role description. Could be "About the role" or maybe "Responsibilities". The posting includes: "While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered." That's location note; maybe we can put in a short paragraph. Then: "At Databricks, our core principles..." etc. That's about company mission. Then: "You will be an essential part of this mission..." etc. Then: "As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations." etc. Then bullet list under "The Impact You Will Have": list of responsibilities. Then "What We Look For": list of requirements. Then "Nice To Have": list of nice-to-have. Then "Interview Process:" maybe not needed? It's process details; could be included maybe under "Interview Process" but not required heading; we can include as a section maybe "Interview Process". However instructions: only include sections when posting has real specific content. It does have interview process details. Could include as a section "Interview Process". But headings list includes: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. They didn't list Interview Process but we can still include if we think it's appropriate? The instruction: "use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." The e.g. suggests those are examples, not exclusive. But they say "Prefer a few substantive sections over many thin ones." Might be okay to include Interview Process as a section if we want. However they might expect only those typical sections. Safer to map content to those headings. We have: - About the role: company mission and role overview. - Responsibilities: The Impact You Will Have bullet list. - Requirements: What We Look For bullet list (mandatory). - Qualifications: maybe education requirement (Bachelor's or Master's degree) could be under Qualifications. - Skills: maybe technical skills list (Python, SQL, etc.) but those are in requirements. Could combine. - Benefits: Benefits section present. - Pay: Pay Range Transparency section with zones. - Schedule: not present; we should not create Schedule section. We should not include empty sections. Thus produce sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. We need to ensure we don't repeat job title as heading. We need to use

• for any list of duties/requirements/benefits. We need to use

  for prose. We must preserve all substantive information; do not invent or summarize away detail. We need to remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. We need to drop Job ID/requisition numbers as headings; fold minor metadata into short

  or drop it. The posting starts with "FEQ427R337 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered." That's a minor metadata line; we can incorporate into a short

  maybe under About the role. We need to keep location encouragement note. Now let's extract substantive content. Paragraphs: 1. "While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered." 2. "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." 3. "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!" 4. "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." Then bullet list under "The Impact You Will Have": - 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". This is process detail; maybe we can include as a short paragraph under About the role or separate section "Interview Process". But not required. Then "#CMEG 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 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 anticipates 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 $152,300—$209,450 USD Zone 2 Pay Range $152,300—$209,450 USD Zone 3 Pay Range $152,300—$209,450 USD Zone 4 Pay Range $152,300—$209,450 USD" Then "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." Then "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." Then EEO etc which we must remove. Thus we need to produce HTML with sections. We need to decide which content goes where. About the role: combine location note, company mission paragraphs, role overview (the Sr. Solutions Engineer paragraph). Possibly also include About Databricks? That could be part of About the role or separate. But we have limited sections; we could include About Databricks as part of About the role. Responsibilities: The Impact You Will Have bullet list. Requirements: What We Look For bullet list (mandatory). Could also include education as part of Requirements or Qualifications. Qualifications: maybe education (Bachelor's or Master's degree) and maybe Nice To Have? But Nice To Have is optional; could be under Qualifications as "Preferred Qualifications". However we have only one Qualifications heading allowed; we could put education there and Nice To Have as part of Qualifications? Might be okay. Skills: maybe we could list technical skills (Python, SQL, Spark, etc.) but they are already in Requirements. Could combine. Benefits: Benefits paragraph. Pay: Pay range details. We should not include Schedule. We need to ensure we don't repeat content. Let's craft. Section 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.

  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