senior data architect

Advansys

<div>Advansys is a dynamic solutions provider focused on delivering smart, modular, and sustainable technology solutions that enhance operations, improve customer experiences, and drive business modernization. With over 400 skilled engineers, we serve 100+ enterprise customers across 14 countries. Specialized in a wide array of premium services including Business Automation, Industrial Digitization, Low code Development, Cloud Services, Warehouse Automation &amp; Strategic Outsourcing.
Founded in 2014, Advansys is part of the INTRO Group, a private conglomerate established in 1980 with diverse investments across different business areas, oil and gas, real estate, specialized engineering, financial investment, Food &amp; manufacturing.
Job Description:<ul>
<li>Contribute in overall modeling standards, guidelines, best practices and approved modeling techniques and approaches.</li>
<li>Contribute in governing the creation of all physical and logical data models in the organization.</li>
<li>Participate in due diligence of new software purchases by reviewing all proposed data models contained in packaged or commercially available applications.</li>
<li>Serve on data integration, business intelligence and content management competency panels or teams.</li>
<li>Participate in all data integration and Enterprise Information Management (EIM) programs and projects &mdash; both enterprise and point-to-point efforts &mdash; by rationalizing data processing for reusable module development.</li>
<li>Work jointly with the data services administrator in developing the data objects and data models to support data services under a service-oriented architecture approach.</li>
<li>Govern the data administration team (modeling, metadata managers and end-user query optimization).</li>
<li>Liaise with the data modeling team, data warehouse team and the application owners in understanding the data interface requirements and help the project team developers to resolve issues related with data requirements. Ensure, gatekeeper functions are effectively defined and managed to reduce data redundancy and increase accuracy.</li>
<li>Contribute in selection of data management tools, and the development of standards, usage guidelines and procedures for those tools.</li>
<li>Document the existing data architecture in a prioritized manner in order to maintain an accurate &lsquo;as is&rsquo; view of the current data environment and define the &ldquo;to be&rdquo; view.</li>
<li>Document the Data Flows / lineage visualizing the &quot;as-is&quot; data movement across key components of the Data landscape and define the &quot;to-be&quot; views.</li>
<li>Work &amp; liaise with various technology and business stakeholders in resolving and escalating issues related with the data solutions and seek their concurrence and approval as per the established process during the SDLC until the solution is deployed.</li>
<li>Provide feedback and improvements over the standards, methodologies, processes and best practices to the enterprise architecture team to review and update enterprise architecture standards both at the group and country level.</li>
<li>Feedback and improve towards corporate metadata management facility.</li>
<li>Work with the Data Quality / Governance teams in understanding areas where data architecture enhancement will assist the overall quality of the Group&rsquo;s data.</li>
<li>Educate senior business representatives in best practices for data quality and to work with them to identify realistic goals and data initiatives.</li> 
</ul> 
 
Requirements 
<ul>
<li>Bachelor's degree in Computer Science, Software Engineering, or a related field.</li>
5 years of experience in data Architecture or Data Modeling 
<li>
</li></ul> 
 
Benefits<ul><li> 
50 Percent of the Salary in USD
</li><li>Social and Medical insurance</li><li>Transportation and transportation allowance</li><li>Internet package</li></ul></div>

Senior Data Architect (Banking Experience)

MGM Resorts International

<div>US, Texas
The SHOW comes alive at MGM Resorts International
Have you ever wondered what it would be like to work in a place full of excitement, diversity, and entertainment? Are you enthusiastic about being a team player in one of the most fascinating industries in the world? At MGM Resorts, we seek individuals like YOU to create unique and show-stopping experiences for our guests.
THE JOB:
The Principal Commercial Data Architect owns the Marketing and Revenue Management data architecture strategy and multi-year roadmap. You will modernize platforms, establish architectural standards, and enable scalable, cloud-native solutions that drive measurable business impact.
You will partner closely with executive leadership, commercial stakeholders, and technology teams to ensure our data platforms are resilient, governed, and built for the future.
THE DAY-TO-DAY:<ul><li>
Define and execute a multi-year Marketing and Revenue Management data architecture roadmap aligned to commercial strategy, including lakehouse evolution, interoperability, governance, and observability</li><li>
Own architectural standards for Databricks, Delta Lake, Unity Catalog, and cloud-native data environments to ensure scalability and performance</li><li>
Architect Marketing and Revenue Management semantic models, KPI logic, and unified metric layers that enable standardized analytics and reporting</li><li>
Lead governance frameworks across metadata, lineage, security, compliance, and regulatory standards</li><li>
Establish Marketing and Revenue Management data observability and quality standards using tools such as Monte Carlo, Soda, and Great Expectations</li><li>
Chair architecture councils and mentor senior architects, strengthening organizational capability and technical excellence</li><li>
Evaluate emerging technologies and guide modernization toward scalable, cloud-native architectures</li></ul>
THE IDEAL CANDIDATE:<ul><li>
10+ years of prior relevant experience in data architecture, engineering, or enterprise data platform leadership</li><li>
5+ years of prior relevant experience in architecting large-scale cloud or Lakehouse environments (Databricks preferred)</li><li>
Deep expertise in lakehouse and distributed systems</li><li>
Hands-on knowledge of Databricks, Delta Lake, and Unity Catalog</li><li>
Strong executive communication and stakeholder influence skills</li><li>
Experience designing governance and compliance frameworks</li><li>
Bachelor&rsquo;s degree in Computer Science, Information Technology, or related field required; Master&rsquo;s preferred</li><li>
Preferred: Domain expertise in Gaming &amp; Hospitality Operations, Loyalty &amp; Customer Engagement, or Marketing &amp; Commercial Analytics</li></ul>
THE PERKS &amp; BENEFITS:<ul><li>
Prioritize your wellness, access programs crafted to nurture your mental and physical health.
</li><li>Enjoy unbeatable discounts on hotel stays, dining, retail, entertainment, and exclusive partner perks for travel, tech, and beyond!
</li><li>Savor delicious meals for free in our employee dining room.
</li><li>Park with ease&mdash;whether you're on or off shift, it's free!
</li><li>From healthcare to financial support and generous time-off options, we&rsquo;ve got you covered.
</li><li>Elevate your career with development programs, connect through networking events, and make a difference with community volunteer opportunities.</li></ul>
VIEW JOB DESCRIPTION:
https://mgmresorts.marketpayjobs.com/ShowJob.aspx?EntityID=2&amp;jobcode=12784
Pay Range:
The pay range for this role is:
$122,700.00 - $163,600.00
This range represents a good faith estimate of the salary range that MGM reasonably expects to pay for the position upon hire. The actual salary offer will take into account a wide range of factors, including location.
This position is eligible to participate in the Company&rsquo;s incentive plan.
Employees in this position are eligible to participate in medical, dental, vision, life insurance, 401(k) plans, and time off plans. Specific program offerings vary by eligibility factors such as geographic location, employment status, and union membership.
Are you ready to JOIN THE SHOW? Apply today!</div>

Principal Commercial Data Architect

Interact Technology Solutions

<div>
 
 Job Summary
 
 
 
 The
 
 Senior AI Data Engineer
 
 is responsible for designing, building, and optimizing enterprise-scale data and AI infrastructure to support machine learning models, generative AI applications, and real-time analytics. The role drives the development of end-to-end data pipelines, from ingestion to production-ready AI data products, ensuring scalability, performance, and compliance across multi-cloud environments.
 
 
 
 Accountability &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and maintain scalable ETL/ELT data pipelines using modern data engineering tools (e.g., Apache Spark, dbt).
 </li>
 <li>
 Architect and implement Lakehouse data platforms (Delta Lake, Apache Iceberg, Apache Hudi) following Medallion architecture (Bronze/Silver/Gold).
 </li>
 <li>
 Develop real-time streaming pipelines using Apache Kafka, Apache Flink, and Spark Structured Streaming.
 </li>
 <li>
 Build and optimize AI/GenAI data pipelines for LLM training, fine-tuning, and inference (tokenization, dataset curation, prompt engineering datasets).
 </li>
 <li>
 Design and implement Retrieval-Augmented Generation (RAG) pipelines, including embedding workflows and vector database integration.
 </li>
 <li>
 Manage feature stores for real-time and batch machine learning use cases.
 </li>
 <li>
 Integrate data pipelines with AI/ML platforms (Databricks MLflow, Azure ML, AWS SageMaker, Vertex AI, OpenAI/Azure OpenAI).
 </li>
 <li>
 Implement data orchestration workflows using Apache Airflow or similar tools with CI/CD pipelines.
 </li>
 <li>
 Ensure data quality, governance, and security using frameworks such as Great Expectations and data catalog tools.
 </li>
 <li>
 Deploy and manage infrastructure using Infrastructure-as-Code tools (Terraform, Bicep, CDK).
 </li>
 <li>
 Collaborate with Data Scientists, ML Engineers, and Solution Architects to deliver production-ready AI solutions.
 </li>
 <li>
 Lead technical design decisions, mentor junior engineers, and contribute to data platform strategy.
 </li>
 <li>
 Maintain documentation, data contracts, and operational runbooks for all pipelines.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 1
 
 &ndash; Required Experience
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Engineering, or related field.
 </li>
 <li>
 4&ndash;5 years of experience in data engineering, with strong exposure to AI/ML data infrastructure.
 </li>
 <li>
 Proven experience building scalable data pipelines and working with large-scale datasets.
 </li>
 <li>
 Hands-on experience with AI/ML platforms and modern data architectures.
 </li>
 <li>
 Experience in regulated industries (e.g., Banking, Telecom, Healthcare) is a plus.
 </li>
 <li>
 Strong problem-solving, analytical thinking, and communication skills.
 </li>
 <li>
 Experience working in cross-functional teams and agile environments.
 
 
 </li>
 </ul>
 
 2&ndash; Technical Skills
 
 
 
 <ul>
 <li>
 Strong SQL and advanced data modeling techniques
 </li>
 <li>
 Apache Spark (PySpark, Spark SQL, Streaming)
 </li>
 <li>
 Python (pandas, PySpark, data processing libraries)
 </li>
 <li>
 Data pipeline orchestration (Apache Airflow)
 </li>
 <li>
 CI/CD for data pipelines (GitHub Actions / Azure DevOps)
 </li>
 <li>
 Lakehouse architectures (Delta Lake / Iceberg / Hudi)
 </li>
 <li>
 Streaming technologies (Kafka, Flink)
 </li>
 <li>
 Cloud platforms (AWS / Azure / GCP)
 </li>
 <li>
 Vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
 </li>
 <li>
 RAG pipeline design and LLM data processing
 </li>
 <li>
 Infrastructure-as-Code (Terraform / Bicep / CDK)
 </li>
 <li>
 Containers (Docker, Kubernetes)
 </li>
 <li>
 Data quality &amp; governance tools
 </li>
 </ul>
</div>

Senior AI Data Engineer

<div>Responsibilities:<ul><li>Develop and maintain conceptual, logical, and physical data models using data modeling tools.</li><li>Collaborate with stakeholders, business analysts, and Data Engineer teams to gather business requirements and define data modeling standards.</li><li>Design and implement data models that support business intelligence, data warehousing, and analytics initiatives.</li><li>Ensure data models adhere to data governance policies, data quality standards, and industry best practices.</li><li>Develop and maintain data model documentation, including data dictionaries, entity-relationship diagrams, and data flow diagrams.</li><li>Participate in data architecture discussions and contribute to the development of the enterprise data architecture.</li></ul>
&bull; Collaborate with database administrators to ensure physical database design aligns with data models. &bull; Stay up-to-date with industry trends, emerging technologies, and data modeling best practices.
Qualifications:<ul><li>Bachelor's degree in Computer Science, Information Systems, or related field.</li><li>5-8 years of experience in data modeling, data architecture, or related field. Proficiency in data modeling.</li><li>Strong understanding of data modeling concepts, including entity-relationship modeling, dimensional modeling, and data normalization.</li><li>Experience using Erwin Data Modeler is a plus.</li><li>Strong analytical, problem-solving, and communication skills.</li><li>Ability to work in a team environment and collaborate with stakeholders.</li></ul></div>

Senior Data Modeler

LN Technologies

Key Responsibilities1. Architecture &amp; Technical Leadership<ul><li>Design end-to-end architectures for AI solutions, IoT platforms, mobile apps, data platforms, and cloud-native systems</li><li>Create architecture diagrams, data models, API specifications, and cloud infrastructure plans</li><li>Define security and compliance frameworks for scalable systems</li><li>Evaluate and recommend emerging technologies aligned with R&amp;D objectives</li><li>Establish architecture standards and best practices across projects</li></ul>2. Project Oversight &amp; Delivery Management<ul><li>Serve as technical lead and solution owner for software development projects</li><li>Collaborate with product managers and engineering teams to break down requirements</li><li>Define technical scope and architecture approach</li><li>Estimate effort and guide sprint planning</li><li>Ensure adherence to code quality, security, and DevOps best practices</li><li>Oversee AI model governance and system integration strategies</li></ul>3. R&amp;D &amp; Innovation Enablement<ul><li>Partner with research teams to translate concepts into technical architectures</li><li>Support technical sections of grant proposals and innovation initiatives</li><li>Prototype new ideas using rapid experimentation and POCs</li><li>Evaluate new frameworks, tools, and platforms for innovation programs</li><li>Drive adoption of emerging technologies in product development</li></ul>4. System Design &amp; Integration<ul><li>Architect scalable cloud-native and microservices-based systems</li><li>Design API-first and event-driven architectures</li><li>Define data platform architectures and integration strategies</li><li>Ensure system scalability, reliability, and performance optimization</li><li>Implement secure system integration across platforms</li></ul>5. Security &amp; Compliance Governance<ul><li>Ensure architecture compliance with security standards (HIPAA, NIST, etc.)</li><li>Define secure authentication, authorization, and data protection models</li><li>Implement risk mitigation strategies in system design</li><li>Enforce cloud security and DevSecOps practices</li></ul>6. Team Management &amp; Leadership<ul><li>Manage and oversee the performance of the engineering and architecture team</li><li>Provide technical mentorship and guidance to team members</li><li>Allocate resources and balance workload across projects</li><li>Conduct performance reviews and support team development plans</li><li>Ensure team adherence to architecture standards and delivery timelines</li><li>Foster collaboration across cross-functional teams</li></ul>7. Stakeholder Collaboration<ul><li>Collaborate with clients, government partners, universities, and internal teams</li><li>Present technical architectures to non-technical stakeholders</li><li>Validate solution feasibility and scalability with cross-functional teams</li><li>Provide technical guidance to engineering and product teams</li></ul>8. Technical Documentation &amp; Knowledge Sharing<ul><li>Document architecture designs and technical decisions</li><li>Prepare architecture guidelines and reusable frameworks</li><li>Conduct knowledge-sharing sessions with engineering teams</li><li>Maintain architecture standards and governance documentation</li></ul>Required Qualifications<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or related field</li><li>7+ years of experience in software architecture or senior engineering roles</li><li>Hands-on experience with cloud platforms (Azure, AWS, or GCP)</li><li>Experience with AI/ML frameworks (TensorFlow, PyTorch, Azure ML, SageMaker)</li><li>Experience with IoT ecosystems and edge computing</li><li>Strong knowledge of API and microservices architecture</li><li>Experience with mobile applications and data platforms</li><li>Experience leading software development teams</li><li>Strong understanding of scalability, security, and system integration patterns</li></ul>Preferred Qualifications<ul><li>Experience with healthcare systems and HIPAA/FDA compliance</li><li>Experience architecting AI systems for real-time data or predictive analytics</li><li>Experience working in R&amp;D or innovation environments</li><li>Relevant certifications (AWS Solutions Architect, Azure Solutions Architect, TOGAF, PMP, etc.)</li></ul>Job Type: Full-timePay: Rs300,000.00 - Rs450,000.00 per monthApplication Question(s):<ul><li>How many years of experience do you have in software architecture or senior development roles?</li><li>Have you led or managed software developers or Project Managers? If yes, please mention the team size.</li><li>What is your current notice period or earliest joining availability?</li><li>Please share your reason for leaving your current/last employer.</li><li>Please share your current salary.</li><li>Please share your expected salary.</li></ul>Work Location: In person

Solution Architect – Emerging Technologies

Arrow Components

<div>
 
 Position
 
 
 
 Senior React Developer (React, TypeScript, Node.js)
 
 
 
 Job Description
 
 
 
 We are looking for a
 
 Senior React Developer
 
 with expertise in
 
 React, Material UI, TypeScript, and Node.js
 
 to help build and optimize high-performance web applications. The ideal candidate has a strong foundation in front-end development best practices, advanced TypeScript skills, and experience with modern JavaScript build tools like Webpack. Experience in Node.js library packaging, design systems, and optimizing front-end performance is highly desirable. This candidate is to lead the design and delivery of modern web experiences built on
 
 React / Next.js
 
 and
 
 Adobe Experience Manager (AEM) Headless
 
 architecture. The architect will define technical strategy, content modeling, and integration patterns to deliver
 
 scalable, performant, and SEO-optimized digital experiences
 
 leveraging a
 
 pure headless CMS
 
 approach.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Define and implement end-to-end architecture using AEM Headless (Content Fragments, GraphQL APIs) and React/Next.js frontends.
 </li>
 <li>
 Architect Server-Side Rendering (SSR), Static Site Generation (SSG), and edge rendering strategies to optimize SEO and performance.
 </li>
 <li>
 Design content models and governance structures that enable omnichannel content reuse.
 </li>
 <li>
 Develop and optimize React components, ensuring reusability, maintainability, and performance.
 </li>
 <li>
 Architect and maintain a scalable React application structure, following best practices for long-term sustainability.
 </li>
 <li>
 Build and package Node.js libraries to be reusable across multiple projects.
 </li>
 <li>
 Write clean, efficient, and scalable TypeScript code, ensuring strong type safety and maintainability.
 </li>
 <li>
 Build UI components using Material UI, ensuring consistency with design guidelines.
 </li>
 <li>
 Integrate and consume RESTful APIs or GraphQL endpoints efficiently.
 </li>
 <li>
 Implement and manage front-end testing using frameworks such as Jest, Cypress, or React Testing Library.
 </li>
 <li>
 Optimize Webpack configurations for faster builds, better bundling, and improved performance.
 </li>
 <li>
 Ensure adherence to best practices for performance optimization, accessibility, and security.
 </li>
 <li>
 Collaborate closely with backend teams to integrate APIs and optimize data fetching strategies.
 </li>
 <li>
 Debug and resolve complex issues across the front-end stack, including state management and caching strategies.
 </li>
 <li>
 Stay updated with the latest trends in React, TypeScript, and front-end development to deliver best-in-class solutions.
 </li>
 <li>
 Participate in code reviews, mentor junior developers, and contribute to technical discussions.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 10+ years of experience in front-end development, with at least 8+ years of hands-on React experience.
 </li>
 <li>
 Advanced TypeScript skills, with a focus on type safety and best practices.
 </li>
 <li>
 Strong experience with Material UI for building accessible, consistent UIs.
 </li>
 <li>
 Solid understanding of Node.js and experience with Node.js library packaging.
 </li>
 <li>
 Hands-on experience with front-end test frameworks (Jest, Cypress, React Testing Library).
 </li>
 <li>
 Deep understanding of Webpack, including performance optimizations, tree shaking, and bundle splitting.
 </li>
 <li>
 Familiarity with state management solutions such as Redux, Zustand, or Recoil.
 </li>
 <li>
 Experience with performance tuning, lazy loading, and optimizing Lighthouse scores.
 </li>
 <li>
 Familiarity with CI/CD pipelines and DevOps practices for front-end deployments.
 </li>
 <li>
 Strong knowledge of RESTful APIs and GraphQL, with experience in efficient data fetching strategies.
 </li>
 <li>
 Excellent problem-solving skills and the ability to debug complex front-end issues.
 </li>
 <li>
 Strong communication skills, with the ability to collaborate effectively with designers, backend developers, and stakeholders.
 
 
 </li>
 </ul>
 
 Must Have Skills
 
 
 
 <ul>
 <li>
 React
 </li>
 <li>
 Material UI
 </li>
 <li>
 TypeScript
 </li>
 <li>
 Storybook
 </li>
 <li>
 SASS
 
 
 </li>
 </ul>
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Senior React Developer (React, TypeScript, Node.js)

The Carlyle Group

<div>
 
 
 Company Profile
 
 
 
 The Carlyle Group (NASDAQ: CG) is a global investment firm with $475 billion of assets under management, across 678 investment vehicles as of March 31, 2026. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,500 professionals operating in 28 offices in North America, Europe, the Middle East, Asia and Australia.
 
 
 
 
 
 Carlyle's purpose is to connect people, ideas, and capital to fuel growth for companies and performance for investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments - Global Private Equity, Global Credit and Carlyle AlpInvest - and has deep expertise across industries, markets, and geographies.
 
 
 
 
 
 At Carlyle, we believe that a wide spectrum of experiences and viewpoints drives performance and success. Our CEO, Harvey Schwartz, has stated that, "To build better businesses and create value for all of our stakeholders, we are focused on assembling leadership teams with the strongest insights from a range of perspectives." Reflecting this view, emphasis is placed on development, retention and inclusion through our internal processes and seven Employee Resource Groups (ERGs). We cultivate a culture where ideas are openly shared and challenged, connecting diverse expertise and perspectives to drive enduring value.
 
 
 
 
 
 
 Fund or Department Description
 
 
 
 The Data &amp; AI Engineer sits within Carlyle's Enterprise Technology &amp; Data organization and supports firm-wide data and AI initiatives spanning investment platforms, portfolio operations, investor relations, and corporate functions. The role operates within a federated data operating model, partnering with domain engineering teams to implement shared platforms and reusable patterns for data and AI under the technical direction of the Senior AI &amp; Data Architect.
 
 
 
 
 
 
 Position Summary
 
 
 
 The Data &amp; AI Engineer is an experienced, hands-on engineer who turns Carlyle's data and AI architecture into working production systems. Reporting to the Senior AI &amp; Data Architect, this role is responsible for building and operating the pipelines, semantic layers, retrieval systems, and AI-ready data products that power analytics, automation, LLMs, agents, and generative AI applications across the firm.
 
 
 
 
 
 The role requires deep, hands-on expertise across modern data engineering and applied AI engineering. The Data &amp; AI Engineer will implement retrieval-augmented generation (RAG) patterns, embedding and indexing pipelines, vector stores, and semantic models alongside core ELT, streaming, and analytical pipelines - treating LLMs, agents, and copilots as first-class consumers of the data platform.
 
 
 
 
 
 This is a senior individual-contributor engineering role that executes against architectural standards, contributes to their evolution through hands-on learning, and partners closely with data science, AI engineering, governance, and domain teams to deliver trusted, AI-consumable data at enterprise scale.
 
 
 
 
 
 
 What Success Looks Like:
 
 In the first 12 months, this role will deliver foundational AI-ready data pipelines and retrieval components defined in the target-state architecture, productionize one or more priority RAG or agent-grounding use cases, and establish reusable engineering patterns that other domain teams can adopt across the federated data platform.
 
 
 
 
 
 
 In-office requirement:
 
 4 days per week
 
 
 
 
 
 
 Primary Responsibilities:
 
 
 
 
 AI Data Pipelines &amp; Retrieval Systems (&asymp;35%)
 
 
 <ul>
 <li>
 Build and operate AI-ready data pipelines - embedding generation, chunking, indexing, and refresh workflows - that make Carlyle's enterprise data reliably retrievable by LLMs, agents, and generative AI applications.
 </li>
 <li>
 Implement retrieval-augmented generation (RAG) components, including vector store integrations, hybrid search, re-ranking, and grounding logic, against architectural patterns defined by the Senior AI &amp; Data Architect.
 </li>
 <li>
 Develop and maintain tool and function interfaces that allow agents and copilots to query and act on enterprise data safely, with appropriate guardrails, logging, and evaluation hooks.
 </li>
 <li>
 Partner with Data Science and AI Engineering teams to operationalize feature stores, evaluation datasets, and reusable AI data products.
 </li>
 <li>
 Contribute to semantic and context engineering work that powers natural-language analytics, conversational reporting, and AI-driven insights for business users.
 </li>
 </ul>
 
 
 
 
 
 Modern Data Pipeline Engineering (&asymp;30%)
 
 
 <ul>
 <li>
 Design, build, and maintain production-grade ELT, streaming, and transformation pipelines using tools such as dbt, Fivetran and Snowflake.
 </li>
 <li>
 Implement ingestion, modeling, and consumption patterns that meet enterprise standards for scalability, performance, security, resiliency, and cost efficiency.
 </li>
 <li>
 Write clean, well-tested Python and SQL; apply software engineering best practices including version control, code review, CI/CD, modular design, and automated testing.
 </li>
 <li>
 Productionize new sources and domains under the federated operating model, partnering with domain data engineers to apply shared platform capabilities consistently.
 </li>
 </ul>
 
 
 
 
 
 Semantic Layer &amp; Data Product Development (&asymp;20%)
 
 
 <ul>
 <li>
 Implement semantic models, data contracts, and analytical/dimensional models that enable trusted self-service analytics and reliable AI grounding.
 </li>
 <li>
 Build and maintain reusable data products with clear ownership, documented contracts, and contextual metadata suitable for both human and AI consumers.
 </li>
 <li>
 Collaborate with the Senior AI &amp; Data Architect to refine and extend enterprise semantic standards based on what works in production.
 </li>
 <li>
 Support discovery and consumption tooling so that analysts, applications, and agents can find and use data products with minimal friction.
 </li>
 </ul>
 
 
 
 
 
 Data Quality, Observability &amp; AI Trust (&asymp;10%)
 
 
 <ul>
 <li>
 Implement data quality checks, lineage capture, and pipeline observability across both data and AI workloads.
 </li>
 <li>
 Build logging, evaluation, and monitoring components for AI systems - including prompt and response capture, retrieval metrics, and model performance signals - in line with governance standards.
 </li>
 <li>
 Partner with Data Governance to operationalize metadata, stewardship, and access controls, ensuring AI systems consume enterprise data with the same rigor as human users.
 </li>
 <li>
 Surface issues early, propose remediations, and feed lessons learned back into architectural patterns.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Engineering Craft (&asymp;5%)
 
 
 <ul>
 <li>
 Participate in architectural design reviews and contribute hands-on engineering perspective to evolving patterns and standards.
 </li>
 <li>
 Mentor junior data engineers and analysts on modern data and AI engineering practices.
 </li>
 <li>
 Document patterns, write runbooks, and share knowledge across the federated organization to accelerate adoption of reusable platform capabilities.
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 
 
 Education &amp; Certifications
 
 
 <ul>
 <li>
 Bachelor's degree, required
 </li>
 <li>
 Concentration in computer science, data engineering, information systems, or a related field, preferred
 </li>
 <li>
 Masters degree, preferred
 </li>
 <li>
 Relevant certifications in cloud, data engineering, analytics, or AI/ML are preferred
 </li>
 </ul>
 
 
 
 
 
 Professional Experience
 
 
 <ul>
 <li>
 6+ years of overall relevant technical experience, required
 </li>
 <li>
 Experience in data engineering, analytics engineering, or platform engineering, with at least 1-2 years of direct, hands-on experience building generative AI or AI/ML systems in production.
 </li>
 <li>
 Proven experience implementing retrieval, grounding, and semantic components for LLM- or agent-based applications, including RAG pipelines, vector stores, embedding workflows, and structured tool use.
 </li>
 <li>
 Hands-on experience with one or more modern AI platforms and tooling categories (e.g., AWS Bedrock, Databricks ML, Snowflake Cortex, OpenAI/Anthropic APIs, LangChain/LlamaIndex or equivalents, MLflow, and vector databases such as Databricks Vector Search, pgvector, or Pinecone).
 </li>
 <li>
 Strong, demonstrable expertise in Python and SQL, with working knowledge of distributed processing frameworks (e.g., Spark).
 </li>
 <li>
 Deep, hands-on experience with modern data stacks - dbt, Fivetran, Snowflake - in AWS-based environments.
 </li>
 <li>
 Track record of building data pipelines and products whose consumers include AI systems, not only BI tools and human analysts.
 </li>
 <li>
 Palantir experience a plus.
 </li>
 <li>
 Experience operating within federated data operating models and complex, regulated enterprise environments; financial services experience preferred.
 </li>
 </ul>
 
 
 
 
 
 Competencies &amp; Attributes
 
 
 <ul>
 <li>
 Demonstrated AI-forward instinct: defaults to asking how AI changes what gets built, rather than whether AI can be added later.
 </li>
 <li>
 Fluency in current AI engineering patterns (RAG, agents, tool use, evaluations, guardrails, observability) and the practical trade-offs involved in shipping them.
 </li>
 <li>
 Strong engineering craft: clean code, automated testing, thoughtful design, and a bias toward production-quality systems over prototypes.
 </li>
 <li>
 Pragmatic, delivery-oriented mindset with strong attention to data quality, AI trust, and long-term maintainability; able to distinguish durable engineering decisions from AI hype.
 </li>
 <li>
 Collaborative partner to architects, data scientists, AI engineers, and domain teams; comfortable operating in a matrixed, federated organization and in high-visibility transformational initiatives.
 </li>
 </ul>
 
 
 
 
 
 Benefits/Compensation
 
 
 
 The compensation range for this role is specific to the applicable office location and takes into account a wide range of factors, including required and preferred skill sets; prior experience and training; and licenses and/or certifications.
 
 
 
 
 
 The anticipated base salary range for this role is $160,000 to $180,000.
 
 
 
 
 
 In addition to base salary, the hired professional will receive a comprehensive benefits package including retirement benefits, health insurance, life and disability insurance, paid time off, paid holidays, family planning benefits, and wellness programs. The hired professional may also be eligible for an annual discretionary incentive program based on individual and organizational performance.
 
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Data & AI Engineer

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