Data Engineer - Senior - Consulting - Location OPEN

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections if posting has real specific content. We must not repeat job title as heading. Remove boilerplate, navigation, legal, EEO, etc. Preserve all substantive info. We need to parse the posting. Key sections: - About the role: The paragraph describing the role: "At EY, we’re all in to shape your future with confidence..." etc. Also "The opportunity The Products and Platforms Practice specializes..." etc. Also "Engineers are problem solvers..." etc. Also "In this role, you will design and build AI and analytics solutions..." etc. Also "Your responsibilities will include creating scalable data architecture..." etc. Also "This role offers the opportunity to work with cutting-edge technologies..." etc. Also "The position may require regular travel to meet with external clients." So we can combine into a prose

maybe multiple paragraphs. - Responsibilities: There is a list under "Your Key Responsibilities As a Senior Data Engineer, you will play a pivotal role..." then bullet list: "Designing, building, and operating scalable on-premises or cloud data architecture.", "Analyzing business requirements and translating them into technical specifications.", "Optimizing data flows for target data platform designs." So we need

• for each. - Skills And Attributes For Success: list of attributes: "Ability to work with both technical and business stakeholders.", "Prior experience leveraging LLMs or other GenAI tooling.", "Proven ability to work across cross-functional teams.", "Proven ability to work with ambiguity or when requirements are lacking/changing.", "Owns a problem from raw source through pipeline, model/analysis, and production handoff.", "Checks bias, leakage, sample size, and whether a metric actually answers the question.", "Writes tested, versioned, observable code — not one-off notebooks that only run on a laptop.", "Strong analytical and decision-making skills.", "Proficiency in cloud computing and data architecture design.", "Experience in data integration and security.", "Ability to manage complex problem-solving scenarios." So we can put under Skills heading. - Qualifications: "To qualify for the role, you must have:" then list: "A Bachelor’s degree required (4-year degree) in Data Science, Machine Learning, Computer Science, Statistics, Mathematics, Engineering, Applied Math, Analytics, or related preferred." "Typically, no less than 2 - 4 years relevant experience." "Hands-on experience developing scalable data solutions using Python, R, and SQL, with expertise in data engineering, data pipelines, streaming architectures, and big data ecosystems." Then a list of many topics: "Cloud Computing Architecture", "Data Architecture Design and Modelling", "Data Integration", "Data Security", "Ontology Design", "Software Engineering", "Data Quality", "Database Management", "Semantic Layer", "Building and Managing Relationships", "Client Trust and Value", "Communicating With Impact", "Hybrid Collaboration", "Complex Problem-Solving", "Critical Thinking". Those seem like qualifications/skills but they are listed after the bullet. We can treat them as part of Qualifications (maybe as a list). Could also be under Skills but they are more like required knowledge areas. We'll put under Qualifications. - Ideally, you’ll also have: list of additional desired qualifications: "A passion for delivering commercial software products and platforms to market", "Deeply technical and constantly in a state of learning", "Able to communicate clearly and efficiently with a variety of audiences including developers, clients, customers, partners and executives", "Fearless in getting “hands-on” with technology and execution", "Strong understanding of modern software engineering processes", "Deep understanding and interest in cloud and distributed systems architectures", "Comfortable with ambiguity with a drive for clarity", "Experience leading and growing technical talent (for software engineering managers)", "Experience in managing change effectively.", "Experience with data quality management.", "Familiarity with semantic layers in data architecture.", "Knowledge of emerging technologies in data analytics." Could be under Qualifications or maybe under Skills. We'll put under Qualifications as "Preferred Qualifications" maybe but we only have headings: Qualifications, Skills. We could split: Qualifications for required, Skills for preferred? But the instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we have Qualifications and Skills separate. We already used Skills for the attributes list. So Qualifications will contain the required and preferred qualifications. - Benefits: The posting mentions "What We Offer You At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers." Then later: "In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options." That's benefits. So we can include Benefits section with that info. - Pay: The posting includes salary ranges: "The salary range for this job is: New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $128,400 to $192,500 Bay Area California offices – $133,600 to $200,600 All other offices locations in the US, including Sacramento – $106,900 to $176,500 Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography." So we need Pay section with that info. - Schedule: Not mentioned explicitly. No schedule info. So we should not include Schedule heading. - Requirements: Could be separate from Qualifications? The instruction includes Requirements as a possible heading. We have Qualifications already. Could we treat Requirements as the same as Qualifications? But we already have Qualifications. Maybe we can put Requirements as the list of required experience/education, and Qualifications as the preferred? However the instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. It doesn't forbid using both Requirements and Qualifications. We need to decide based on content. The posting has "To qualify for the role, you must have:" which is requirements. Then "Ideally, you’ll also have:" which is preferred qualifications. So we can have Requirements heading for the must-haves, and Qualifications heading for the ideal/additional. Or we could combine. The instruction says "include a section ONLY when the posting has real, specific content for it". So we can have both if content distinct. Thus: - About the role: prose. - Responsibilities: list. - Requirements: list of must-haves (Bachelor's degree, 2-4 years experience, hands-on experience with Python,R,SQL, expertise in data engineering etc). Could also include the list of specific technical areas (Cloud Computing Architecture, Data Architecture Design and Modelling, etc) as part of requirements? Those are listed after the hands-on experience line; they could be considered required knowledge areas. We'll include them under Requirements as list. - Qualifications: list of ideal/additional (passion for delivering commercial software, deeply technical, etc). Could also include the "Ideally, you’ll also have:" list. - Skills: list of attributes (Ability to work with both technical and business stakeholders, etc). We'll put that. - Benefits: prose about total rewards. - Pay: salary ranges. We must not include boilerplate like EEO, legal, application instructions, etc. Remove lines like "Are you ready to shape your future with confidence? Apply today." etc. Also remove "To make the most of your application experience..." etc. Also remove "EY | Building a better working world" etc. Also remove EEO statements. We need to output only HTML fragment, no /, no markdown. We'll produce something like:

  About the role

  At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. At EY, our purpose is to shape the future. The insights and quality services we provide help build trust and confidence in the capital markets and economies all over the world. We develop outstanding leaders who are teamed to deliver our promises to all our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for our communities. The Products and Platforms Practice specializes in mission-critical, intelligent platforms for the world’s most ambitious organizations. Using our product-driven, AI-centric approach, we empower organizations to build for the intelligent digital future. Our elite team of product leaders, data scientists, designers, and software engineers enable our clients to solve their most complex product challenges and positively impact people and the world. Engineers are problem solvers. While most have deep expertise in specific areas of the technology stack (front end, back end, data, security etc.), all are comfortable swimming across lanes. This is really important in delivering the product and platform outcomes that our customers expect. In this role, you will design and build AI and analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that technical requirements align with business needs. Your responsibilities will include creating scalable data architecture and modeling solutions that support the entire data asset lifecycle. This role offers the opportunity to work with cutting-edge technologies and stay ahead of industry trends, ensuring you gain a competitive advantage in the market. The position may require regular travel to meet with external clients.

  Responsibilities

  • Designing, building, and operating scalable on-premises or cloud data architecture.
  • Analyzing business requirements and translating them into technical specifications.
  • Optimizing data flows for target data platform designs.

  Requirements

  • A Bachelor’s degree required (4-year degree) in Data Science, Machine Learning, Computer Science, Statistics, Mathematics, Engineering, Applied Math, Analytics, or related preferred.
  • Typically, no less than 2 - 4 years relevant experience.
  • Hands-on experience developing scalable data solutions using Python, R, and SQL, with expertise in data engineering, data pipelines, streaming architectures, and big data ecosystems.
  • Cloud Computing Architecture
  • Data Architecture Design and Modelling
  • Data Integration
  • Data Security
  • Ontology Design
  • Software Engineering
  • Data Quality
  • Database Management
  • Semantic Layer
  • Building and Managing Relationships
  • Client Trust and Value
  • Communicating With Impact
  • Hybrid Collaboration
  • Complex Problem-Solving
  • Critical Thinking

  Qualifications

  • A passion for delivering commercial software products and platforms to market
  • Deeply technical and constantly in a state of learning
  • Able to communicate clearly and efficiently with a variety of audiences including developers, clients, customers, partners and executives
  • Fearless in getting “hands-on” with technology and execution
  • Strong understanding of modern software engineering processes
  • Deep understanding and interest in cloud and distributed systems architectures
  • Comfortable with ambiguity with a drive for clarity
  • Experience leading and growing technical talent (for software engineering managers)
  • Experience in managing change effectively
  • Experience with data quality management
  • Familiarity with semantic layers in data architecture
  • Knowledge of emerging technologies in data analytics

  Skills

  • Ability to work with both technical