Jobs · Consulting

Databricks Data Architect

Lumenalta · United States · 4 wk ago
RemoteRemoteConsulting$90k–$130k/yrFull-time
We need to output HTML fragment with sections: About the role (but we should not repeat job title; we have heading "About the Role" in the source; we need to use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. The source includes "About the Role" section, then "What You’ll Do" (responsibilities), "What We’re Looking For" (requirements/qualifications/skills), "Why Lumenalta is an amazing place to work at" (benefits?), "Our Process" (maybe not needed), "Salary" (pay), "Location:" (maybe schedule? Not exactly), "Benefits" (list), "Position Details" (schedule?), "Application Deadline" (maybe drop as boilerplate). We must remove cookie/navigation/legal/EEO etc. Also remove application instructions. So we need to keep substantive info. We need to decide which sections to include: About the role (we have content), Responsibilities (What You’ll Do), Requirements (What We’re Looking For includes experience, skills, qualifications), maybe Qualifications separate? Could combine. Benefits: we have Benefits list. Pay: Salary range. Schedule: Position Details says full-time 40 hours per week Monday-Friday. That's schedule. We should not include sections with placeholder or vague. All content is specific. We must not repeat job title as heading. No Job ID. We must output only HTML fragment, no /, no markdown fences. We'll produce something like:

About the role

... (the paragraph(s) from About the Role)

Responsibilities

  • ... each bullet from What You’ll Do

Requirements

  • ... each bullet from What We’re Looking For (maybe split into experience, Unity Catalog expertise, etc.)
Optionally also have

Qualifications

but we can combine. But instructions: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should use those exact headings if we have content. We have content for About the role, Responsibilities, Requirements (maybe also Qualifications and Skills). We could split What We’re Looking For into Requirements (experience), Qualifications (certifications, citizenship), Skills (technical). But we can also just put all under Requirements. However to follow instruction, we should create sections only when posting has real specific content. It does have content for each of those categories. Let's parse: What We’re Looking For includes: - 8+ years across solutions architecture, data engineering, or related roles, including multiple production Databricks platform architectures on AWS. At least one should be in a regulated or export-controlled environment. (Experience) - Deep, hands-on Unity Catalog expertise. You have implemented row filters, column masks, and attribute-based access control in production and can explain the trade-offs of each. (Skill) - Practical experience translating regulatory requirements (CUI, ITAR, or equivalent classification regimes) into enforceable data policy. (Skill/Experience) - Working knowledge of Delta Lake internals, Lakehouse Federation, Delta Sharing, and Databricks Workflows sufficient to make and defend design decisions under questioning. (Skill) - Demonstrated ownership of platform cost: you have written cluster and budget policies and built a chargeback model. (Skill) - Strong technical writing. Architecture documents, assessment reports, and executive decks are core deliverables here, reviewed by the client and by enterprise security. (Skill) - Experience running structured discovery independently across large enterprise stakeholder groups, synthesizing conflicting input into clear decisions. (Skill) - A skilled communicator with the presence to lead technical conversations, align stakeholders, and drive decisions in complex, multi-team environments. (Skill) - Databricks Data Engineer Professional certification, or willingness to obtain it before start. (Qualification) - US citizenship and ability to pass a background check. (Qualification) - Fluent English, both written and spoken. (Skill) Thus we can have Requirements (experience), Qualifications (certification, citizenship, language), Skills (the rest). But we could also combine. Benefits: list includes flexible working hours, health insurance, 401K Contribution, professional development fund, 15 days PTO, access to soft-skill development courses. Pay: Salary range: $90,000 - $130,000 annually. Schedule: Position Details: full-time position requiring a minimum of 40 hours per week, Monday through Friday. We should also include Location? Not required as heading; but we could include location in About the role paragraph? The posting includes "Location: This is a fully remote position. This position supports a U.S. Government contract that requires all personnel to possess U.S. Citizenship. Availability to work overlapping Pacific, Central, or Eastern U.S. time zones." That's location info; we could embed in About the role paragraph or maybe a separate section? Not required heading. We'll include in About the role paragraph. We must remove boilerplate like "Actively hiring", "Our Process", "Application Deadline", etc. Now craft HTML. We need to preserve all substantive information; do not invent or summarize away detail. So we need to keep the details exactly as given, but we can rephrase into HTML list items; but must preserve meaning. We can copy sentences. Let's extract About the Role paragraph(s): Original: "About the RoleWe partner with global enterprises to design and build large-scale data platforms that power the products and operations at the center of their business. This engagement is a Databricks lakehouse foundation for a US defense manufacturer, which is establishing Databricks as the central platform for their engineering and manufacturing data. Most of that data is export-controlled. Access cannot be a per-table exercise here; it has to derive from classification, which means governance is not a layer added later: it is the architecture. You will build the classification model, express it as a Unity Catalog policy, and defend it to enterprise security reviewers. This is a technical leadership role. You will lead through architecture, technical credibility, and influence, with one senior engineer on the team alongside you. Two people on the engagement means you own the architecture and governance end to end, run stakeholder discovery yourself, and present without an account team in between. The engagement opens with a discovery and architecture phase: assess the current landscape, prioritize use cases, and author the target-state design, governance model, and implementation roadmap. It then moves into the build, executing what you wrote." We need to keep that as prose in

. Possibly split into multiple paragraphs but okay. Now Responsibilities: "What You’ll Do" bullet list: - Lead discovery across the client's data, engineering, security, and business teams, documenting data movement, security architecture, integration topology, and platform configuration, and setting the cadence, RACI, and communication plan. - Prioritize the work by facilitating use case sessions and scoring candidates on business value, technical complexity, and data readiness. - Design the target-state Lakehouse architecture, including medallion design across structured relational sources, Delta Lake patterns (managed versus external tables, predictive optimization, liquid clustering), orchestration in Databricks Workflows, and federate-versus-ingest decisions per source using Lakehouse Federation. - Own the Unity Catalog governance blueprint: metastore topology, row filters, column masks, attribute-based access control, governed tags, and lineage, with CUI and ITAR classification expressed as tag-driven policy so access derives from classification rather than per-table maintenance. - Apply FinOps discipline through budget and cluster policies, serverless spend management, and chargeback tagging, alongside data quality monitoring standards and the semantic layer. - Present to enterprise security reviewers and carry the architecture through their process. - Author the deliverables: current-state assessment, target-state architecture, implementation roadmap, and the executive readout to client leadership. - Lead the build, implementing the architecture on AWS, including GovCloud deployment where required, workspace topology, network isolation, identity integration, Unity Catalog governance, and Delta Sharing across regulatory boundaries. - Set technical direction for the ingestion engineer, review their work, and unblock them on source system and platform issues. We'll put each as

  • . Now Requirements (experience): maybe just the first bullet about 8+ years. But we could also include "At least one should be in a regulated or export-controlled environment." as part of that. We'll put:
  • 8+ years across solutions architecture, data engineering, or related roles, including multiple production Databricks platform architectures on AWS. At least one should be in a regulated or export-controlled environment.
  • Now Qualifications: Databricks Data Engineer Professional certification, or willingness to obtain it before start. US citizenship and ability to pass a background check. Fluent English, both written and spoken. We'll list each as
  • . Now Skills: the rest of the bullets from What We’re Looking For (excluding the experience, qualification, language). Let's list: - Deep, hands-on Unity Catalog expertise. You have implemented row filters, column masks, and attribute-based access control in production and can explain the trade-offs of each. - Practical experience translating regulatory requirements (CUI, ITAR, or equivalent classification regimes) into enforceable data policy. - Working knowledge of Delta Lake internals, Lakehouse Federation, Delta Sharing, and Databricks Workflows sufficient to make and defend design decisions under questioning. - Demonstrated ownership of platform cost: you have written cluster and budget policies and built a chargeback model. - Strong technical writing. Architecture documents, assessment reports, and executive decks are core deliverables here, reviewed by the client and by enterprise security. - Experience running structured discovery independently across large enterprise stakeholder groups, synthesizing conflicting input into clear decisions. - A skilled communicator with the presence to lead technical conversations, align stakeholders, and drive decisions in complex, multi-team environments. We'll put each as
  • under Skills. Now Benefits: list: - Flexible working hours in a remote environment. - Health insurance (medical and dental) for W2 Employees. - 401K Contribution. - A professional development fund to enhance your skills and knowledge. - 15 days of paid time off annually. - Access to soft-skill development courses to further your career. We'll put each as
  • . Now Pay: Salary range: $90,000 - $130,000 annually, with final compensation determined by your qualifications, expertise, experience, and the role's scope. We'll put in

    . Now Schedule: Position Details: This is a full-time position requiring a minimum of 40 hours per week, Monday through Friday. We'll put in

    . We might also include location info in About the role paragraph; we can add a sentence: "This is a fully remote position supporting a U.S. Government contract requiring U.S. Citizenship and availability to work overlapping Pacific, Central, or Eastern U.S. time zones." We'll incorporate that into About the role paragraph. Now ensure we don't include any boilerplate like "Actively hiring", "Our Process", "Application Deadline", etc. Now produce HTML. We need to use

    for each section heading. We'll output:

    About the role

    ...

    Responsibilities

      ...

    Requirements

      ...

    Qualifications

      ...

    Skills

      ...

    Benefits

      ...

    Pay

    ...

    Schedule

    ...

    Make sure no extra text. Let's craft the About the role paragraph: "We partner with global enterprises to design and build large-scale data platforms that power the products and operations at the center of their business. This engagement is a Databricks lakehouse foundation for a US defense manufacturer, which is establishing
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