Data Architect

We need to output HTML fragment with sections: About the role (already present), Responsibilities, Requirements (maybe Qualifications), Skills, maybe Preferred Qualifications? The instruction: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Include a section ONLY when posting has real, specific content for it. So we need to parse the posting. We have: Title line: Data Architect (Databricks & Asset Analytics) Remote role with Rail Industry based in Washington DC. Duration: 12 months contract Ideal candidate should have experience working with Capital projects and Asset Management. Must have active Linkedin 2020 or before. Strong Comm Skills Snr folks 14+ yrs. Rail and transportation industry exp pref first. Then "About The Role" paragraph. Then "Key Responsibilities" list. Then "Required Qualifications" list. Then "Required Skills" list. Then "Preferred Qualifications" list. Then "Databricks Certifications" list. Then "Ideal Candidate Profile" paragraph. We need to map to headings: About the role (we have About The Role). Responsibilities (Key Responsibilities). Requirements (maybe Required Qualifications). Qualifications? Could combine Required Qualifications and Preferred Qualifications? The instruction says we can have sections like Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which sections to include based on content. We have Required Qualifications (specific). We have Required Skills (specific). We have Preferred Qualifications (specific). We have Databricks Certifications (specific). We have Ideal Candidate Profile (maybe could go under About the role or separate? Could be a summary; but we can include as a paragraph under About the role? The instruction: "Prefer a few substantive sections over many thin ones." So we might combine some. We need to avoid repeating job title as heading. Also avoid Job ID etc. We need to remove boilerplate: cookie/navigation/legal/EEO etc. Not present. We need to preserve all substantive information. We need to output only HTML fragment. Thus produce something like:

About the role

... (the About The Role paragraph)

Responsibilities

• ...
...

Requirements

• ...
...

Skills

• ...
...

Preferred Qualifications

• ...
...

Certifications

• ...
...

Maybe also include Ideal Candidate Profile as a paragraph under About the role or separate? Could be its own section "Ideal Candidate Profile" but not in the list of allowed headings; but we could treat as part of About the role. However the instruction says use headings from the list; but we can also add other headings if needed? It says "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 "include a section ONLY when the posting has real, specific content for it". So we could add Ideal Candidate Profile as a heading if we want, but better to stick to allowed ones to be safe. We could incorporate Ideal Candidate Profile into About the role paragraph. Thus we will have sections: About the role, Responsibilities, Requirements, Skills, Preferred Qualifications, Certifications. But we also have Required Qualifications and Required Skills separate. Could combine Required Qualifications into Requirements, and Required Skills into Skills. Preferred Qualifications as its own section. Certifications as its own. We must preserve all substantive information: need to include each bullet. Let's extract content. About The Role paragraph: "The Data & AI Solutions Delivery Lead will drive the strategy, architecture, and end-to-end delivery of enterprise Data, Analytics, AI, and Business Intelligence solutions on the Databricks Lakehouse Platform. This role is heavily focused on Asset Analytics, enabling data-driven decision making for infrastructure asset management, reliability engineering, predictive maintenance, capital planning, and operational risk reduction.The ideal candidate will combine deep expertise in Databricks, Data Engineering, and AI/ML with hands-on experience in asset-intensive industries such as rail, transportation, utilities, manufacturing, energy, or other linear asset environments. The individual will lead cross-functional teams in transforming operational, maintenance, inspection, and condition-monitoring data into actionable business intelligence and advanced predictive insights." We might also include the earlier paragraph about role? Actually there is also initial description: "Title: Data Architect (Databricks & Asset Analytics) Remote role with Rail Industry based in Washington DC. Duration: 12 months contract Ideal candidate should have experience working with Capital projects and Asset Management. Must have active Linkedin 2020 or before. Strong Comm Skills Snr folks 14+ yrs. Rail and transportation industry exp pref first." This is metadata; we should fold minor metadata into a short

or drop it. The instruction: "do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So we could include a short paragraph at top with that info, but not as a heading. However we also have About the role heading; we could place that metadata before the About the role heading as a

. But we need to preserve all substantive information; is that substantive? It includes duration, location, contract, LinkedIn requirement, communication skills, seniority, industry preference. That's substantive. So we should include it as a paragraph before About the role heading. Thus output:

Data Architect (Databricks & Asset Analytics) – Remote role with Rail Industry based in Washington DC. Duration: 12 months contract. Ideal candidate should have experience working with Capital projects and Asset Management. Must have active LinkedIn profile from 2020 or earlier. Strong communication skills. Senior folks with 14+ years experience. Rail and transportation industry experience preferred.

Then

About the role

and paragraph. Now Responsibilities: list from "Key Responsibilities". Need to capture each bullet. Let's extract: - Lead the design, development, and delivery of enterprise Data, Analytics, AI, and Business Intelligence solutions utilizing the Databricks Lakehouse Platform. - Architect and optimize scalable data pipelines leveraging Databricks Workflows, Delta Lake, Delta Live Tables, Unity Catalog, and Medallion Architecture. - Establish DevOps and CI/CD best practices through Databricks Asset Bundles (DAB), Git integration, deployment automation, and environment management. - Design and implement Asset Analytics solutions that provide deeper visibility into asset condition, reliability, performance, and lifecycle costs. - Develop advanced predictive analytics and machine learning models supporting: - Asset Health Monitoring - Failure Prediction & Root Cause Analysis - Remaining Useful Life (RUL) Estimation - Predictive & Prescriptive Maintenance - Reliability Centered Maintenance (RCM) - Critical Asset Risk Management - Asset Performance Optimization - Asset Lifecycle Forecasting - Build analytical frameworks that evaluate asset risk, maintenance effectiveness, asset criticality, and investment prioritization. - Develop risk-based models supporting capital planning, infrastructure investment strategies, asset replacement planning, and long-term maintenance programs. We need to format as

• . For nested list under Develop advanced predictive analytics..., we could either keep as separate items or embed sublist. Simpler: make each sub-bullet as separate
• under same parent? Could nest
  inside
  • . That's allowed. We'll do that. Now Required Qualifications: - 7+ years of experience in Data Engineering, Data Analytics, Data Science, Asset Analytics, or Enterprise Data Platforms. - 3+ years of experience leading large-scale Data, Analytics, AI, or Digital Transformation initiatives. - Strong hands-on experience with Databricks, Spark, Delta Lake, and modern cloud-native data platforms. - Experience delivering AI/ML, predictive analytics, business intelligence, and enterprise-scale reporting solutions. - Proven experience building asset health, reliability, maintenance, risk, or performance management analytics solutions. - Expertise in SQL, Python, PySpark, and modern data engineering practices. - Experience with cloud platforms such as Azure, AWS, or Google Cloud. Now Required Skills (list): - Databricks Lakehouse Platform - Data Engineering - Delta Lake & Medallion Architecture - Asset Analytics - Data Science & AI/ML - Predictive Maintenance - Reliability Engineering - Risk Analytics - PySpark & Python - SQL - Databricks Workflows - Unity Catalog - MLflow - Delta Live Tables - CI/CD & Databricks Asset Bundles (DAB) Now Preferred Qualifications: - Experience in rail, transportation, infrastructure, utilities, energy, manufacturing, or other asset-intensive industries. - Experience supporting linear asset environments such as rail networks, track infrastructure, roadways, pipelines, telecommunications, or utility transmission systems. - Strong knowledge of asset management frameworks including ISO 55000. - Experience with condition monitoring systems, IoT platforms, SCADA systems, telemetry, and sensor-based analytics. - Understanding of maintenance engineering methodologies including RCM, FMEA, Asset Criticality Analysis, and Risk-Based Maintenance. - Experience supporting capital planning, investment prioritization, and infrastructure lifecycle management programs. Now Databricks Certifications: - Databricks Certified Data Engineer Associate/Professional - Databricks Certified Machine Learning Associate/Professional - Databricks Certified Generative AI Engineer Now Ideal Candidate Profile paragraph: "The ideal candidate blends strong technical leadership in Databricks and AI/ML with deep knowledge of Asset Analytics, helping organizations optimize asset reliability, reduce maintenance costs, improve operational performance, extend asset lifecycles, and make data-driven capital investment decisions across large-scale infrastructure environments." We could incorporate this as a paragraph under About the role or as its own section "Ideal Candidate Profile". Since not in list, maybe add as a paragraph after About the role. But we already have About the role paragraph; we could append this as another paragraph under same heading. That would preserve info. Thus final HTML:

    Data Architect (Databricks & Asset Analytics) – Remote role with Rail Industry based in Washington DC. Duration: 12 months contract. Ideal candidate should have experience working with Capital projects and Asset Management. Must have active LinkedIn profile from 2020 or earlier. Strong communication skills. Senior folks with 14+ years experience. Rail and transportation industry experience preferred.

    About the role

    The Data & AI Solutions Delivery Lead will drive the strategy, architecture, and end-to-end delivery of enterprise Data, Analytics, AI, and Business Intelligence solutions on the Databricks Lakehouse Platform. This role is heavily focused on Asset Analytics, enabling data-driven decision making for infrastructure asset management, reliability engineering, predictive maintenance, capital planning, and operational risk reduction.The ideal candidate will combine deep expertise in Databricks, Data Engineering, and AI/ML with hands-on experience in asset-intensive industries such as rail, transportation, utilities, manufacturing, energy, or other linear asset environments. The individual will lead cross-functional teams in transforming operational, maintenance, inspection, and condition-monitoring data into actionable business intelligence and advanced predictive insights.

    The ideal candidate blends strong technical leadership in Databricks and AI/ML with deep knowledge of Asset Analytics, helping organizations optimize asset reliability, reduce maintenance costs, improve operational performance, extend asset lifecycles, and make data-driven capital investment decisions across large-scale infrastructure environments.

    Responsibilities

    • Lead the design, development, and delivery of enterprise Data, Analytics, AI, and Business Intelligence solutions utilizing the Databricks Lakehouse Platform.
    • Architect and optimize scalable data pipelines leveraging Databricks Workflows, Delta Lake, Delta Live Tables, Unity Catalog, and Medallion Architecture.
    • Establish DevOps and CI/CD best practices through Databricks Asset Bundles (DAB), Git integration,