senior data architect

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you a Data Engineering and Architecture specialist? Do you have experience designing and building Data Lakes, Data Warehouses, and scalable data platforms in the cloud? Do you want to help Public Sector customers deploy mission-critical data and ML solutions at scale? Are you detail-oriented, creative, and collaborative? Then this is the position for you.<br>
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As a Delivery Consultant specializing in Data Engineering &amp; Architecture, you will provide exceptional technical design and thought leadership for cloud data applications, working with a world-class team serving federal, state, local government, and national security customers. You will design, build, and optimize data architectures and platforms that help organizations achieve their missions through data-driven decision making. You will gain the opportunity to learn from, collaborate with, and educate some of the brightest technical minds in the industry across the breadth of enterprise data architecture.<br>
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The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.<br>
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This is a customer-facing role. You will work from one of the listed locations (or customer sites) Monday through Friday each week. Travel to client locations to deliver professional services may be required. This is not a remote position.<br>
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This position requires that the candidate selected be a US Citizen and currently possess and maintain an active Top Secret security clearance.<br>
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Key job responsibilities<br>
As an experienced data professional, you will be responsible for:<br>
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<ul><li>Helping clarify customer business outcomes during project discovery and translating them into data architecture and engineering solutions</li><li>Designing and building data analytics applications that are secure, scalable, reliable, performant, and cost-effective</li><li>Collaborating with stakeholders to gather requirements, assess current infrastructure, and propose effective data migration and modernization strategies</li><li>Identifying, mitigating, and communicating risks related to solution and service constraints by making informed technical trade-offs</li><li>Acting as a trusted advisor to customers on industry trends, emerging data technologies, and innovative solutions</li><li>Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts</li></ul><br>
About the team<br>
Diverse Experiences
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Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
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Why AWS
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Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
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Work/Life Balance
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We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud.
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Inclusive Team Culture
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Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
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Mentorship and Career Growth
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We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
</div><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>Bachelor's degree in computer science, engineering, mathematics or equivalent</li><li>5+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience</li><li>Experience with SQL, Python, schema definition, and software engineering best practices including secure, testable, and maintainable code</li><li>Understanding of distributed systems, data integration techniques (ETL vs. federation), database optimization (partitioning, indexing), and relational database performance tuning</li><li>Current, active US Government Security Clearance of Top Secret or above</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience building data platforms with AWS services such as Glue, Lake Formation, Athena, Kinesis, and Lambda</li><li>Experience with CI/CD automation (CDK or Terraform), physical data modeling (Dimensional, Data Vault), and data pipeline optimization</li><li>Experience leading end-to-end data engineering projects including migrating on-premises data applications to cloud-native architectures</li><li>Experience interfacing with customers at different organizational levels to translate requirements into scalable data architectures</li><li>Knowledge of security and compliance standards (e.g., FedRAMP, NIST, HIPAA)</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
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Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually<br>
USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually</div><p></p>

Senior Data Engineer/Architect, WWPS ProServe Data and Machine Learning

The Value Maximizer

<div>
 We are seeking an experienced Senior Data Engineer / Data Architect with deep expertise in financial services and capital markets trading systems to design, build, and operate highly scalable, low latency data platforms. This role focuses on creating modern data lakehouse architectures, real time data pipelines, and analytics ready data models that support trading, risk, reporting, and regulatory requirements.The ideal candidate brings strong technical depth in distributed data systems, hands on experience with streaming and batch pipelines, and a solid understanding of trade lifecycle, market data, and regulatory compliance. You will work closely with trading desks, product teams, AI/analytics teams, and architects to deliver reliable, secure, and high performance data solutions.
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 <strong>
  Job Title: Senior Data Engineer / Data Architect - Capital Markets
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  Location: San Diego, CA
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  Domain: Financial Services - Capital Markets / Trading Systems
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  Required Qualifications:
  <br/>
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 <ul>
  <li>
   7-12+ years of experience in data engineering, backend engineering, or distributed systems&middot; Strong programming expertise in Python, Scala, and/or Java&middot; Advanced SQL skills and hands on experience with distributed data processing frameworks such as Apache Spark or Apache Flink&middot; Extensive experience with streaming platforms including Kafka, Kinesis, or Pulsar&middot; Hands on experience with data lake and data warehouse technologies such as Databricks, Snowflake, Amazon Redshift, or similar platforms&middot; Proven experience building real time or near real time data pipelines&middot; Strong understanding of data modeling, distributed systems, scalability, and performance optimization Preferred Qualifications
  </li>
  <li>
   Experience in Wealth Management or Capital Markets trading systems&middot; Familiarity with OMS/EMS platforms such as Charles River Development (CRD), Aladdin, FIS, or similar systems&middot; Strong knowledge of market data across equities, fixed income, derivatives, and other asset classes&middot; Understanding of the trade lifecycle, including order capture, execution, allocation, clearing, and post trade processing&middot; Experience with cloud native data platforms on AWS, Azure, or GCP&middot; Exposure to real time analytics, risk management systems, and regulatory reporting platforms
  </li>
 </ul>
</div>


Senior Data Engineer / Data Architect

Interact Technology Solutions

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

Qiddiya Investment Company

<div><p>Qiddiya Investment Company is excited to announce a new opportunity for an Assistant Manager - Data &amp; AI Architect. In this pivotal role, you will be at the forefront of integrating advanced data management and artificial intelligence solutions to support our innovative projects and initiatives. You will work closely with cross-functional teams to design and implement cutting-edge data architectures that leverage AI technologies, driving data-driven decision-making and enhancing user experiences.</p><p>
Your expertise in data strategy, architecture design, and AI applications will be instrumental in harnessing the power of data to unlock insights and create enhanced value across our organization.</p>
Responsibilities<ul>
<li>Design and implement robust data architectures that effectively integrate data management and AI technologies.</li>
<li>Develop and oversee the deployment of AI models and analytics solutions to support operational efficiencies and predictive analytics.</li>
<li>Collaborate with business units to identify opportunities for leveraging AI to enhance business processes and customer experiences.</li>
<li>Ensure data governance and security measures are in place for AI models and data solutions.</li>
<li>Conduct regular assessments of technology trends to inform strategic data and AI direction.</li>
<li>Mentor and provide technical leadership to the data and analytics teams, fostering a culture of innovation and continuous improvement.</li>
<li>Develop standards and best practices for data architecture and AI implementation across projects.</li>
<li>Coordinate with IT infrastructure teams to ensure that data environments are optimized for analytics and AI workloads.</li>
<li>Work with data scientists and analysts to translate business needs into functional AI solutions.</li>
<li>Monitor and evaluate AI solution performance and make adjustments as necessary to enhance effectiveness.</li>
<li>Facilitate training sessions on data management and AI integration for relevant stakeholders.</li><br>
</ul><br>
<br>
<b>Requirements</b><br>
<ul><li>
Bachelor&rsquo;s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
</li><li>Minimum of 4<b> years of experience</b> in data architecture, data engineering, or AI development roles.
</li><li>Strong expertise across the <b>enterprise</b> <b>data, analytics, and AI platform landscape</b>, with hands-on experience across the full technology stack including modern architectures and best practices.
</li><li>Proven ability to lead <b>end-to-end architecture and solution design</b>, and to build <b>scalable, enterprise-grade data platforms</b> for large, complex organizations</li></ul></div>

Assistant Manager - Data & AI Architect

Kearney

<div><h3 class="jobSectionHeader"><b>Job Description</b></h3><p></p><div><div><p><b>
About Kearney Activate</b></p></div><div><p>
Kearney Activate is the business acceleration and enablement arm of Kearney Management Consulting, helping clients accelerate transformation through Data and AI.</p></div><div><p>
Our Data &amp; AI business line bridges strategy, technology, and execution to deliver data-driven, AI-enabled, and cloud-powered transformations. We partner with leading platforms such as Microsoft, AWS, Snowflake, Databricks and Nvidia to help organizations build trusted data foundations, deploy intelligent solutions, and scale innovation.</p></div><div><p>
We operate across four key focus areas:</p></div><div><ul><li><div>
Advisory &amp; Assurance Services: Driving strategy, governance, and change management to ensure impactful transformation.</div></li></ul></div><div><ul><li><div>
Data Services: Building trusted, high-quality data foundations using Agentic AI across engineering, architecture, and governance.</div></li></ul></div><div><ul><li><div>
Insights Services: Unlocking value through analytics, data science, and AI-driven storytelling for better decision making.</div></li></ul></div><div><ul><li><div>
Asset Services: Developing reusable GenAI assets, accelerators, and AI-powered solutions that push the boundaries of innovation.</div></li></ul></div><div></div><div><p><b><br>
Position Overview</b></p></div><div><p>
We are seeking a visionary AI-Enabled Solution Architect to help lead the regional design and delivery of next-generation, AI-native data and analytics solutions. This role is central to our transformation team as we embed Generative AI, Agentic Intelligence, and modern data engineering into the core of how we operate and deliver value to our clients.</p></div><div><p>
You&rsquo;ll not only shape cutting-edge architectures but also lead and inspire multidisciplinary teams, helping to develop the next generation of technical leaders who carry our depth of expertise into complex client environments. You'll operate at the intersection of technology and business, translating emerging capabilities into practical, high-impact solutions.</p></div><div><p><b>
Your Responsibilities</b></p></div></div><div><div><ul><li><div>
Architect scalable, modular platforms that integrate modern data engineering with GenAI and Agentic AI capabilities.</div></li></ul></div><div><ul><li><div>
Design and build end-to-end ingestion, transformation, and classification pipelines across structured and semi structured data sources (e.g., Excel, JSON).</div></li></ul></div><div><ul><li><div>
Implement RAG (Retrieval-Augmented Generation) pipelines using intelligent chunking strategies and multimodal retrieval (e.g., BM25, dense vector search, graph-based, structured data, and vision-based inputs).</div></li></ul></div><div><ul><li><div>
Drive data quality through embedded validation, monitoring, and automated reporting frameworks.</div></li></ul></div><div><ul><li><div>
Enable in-context learning and enterprise-scale agent design using different prompting techniques (like ReAct, Tree-of-Thoughts, Reflexion, or hybrid reasoning patterns) for automation, insight generation, and decision support.</div></li></ul></div><div><ul><li><div>
Lead exploratory data analysis (EDA), dynamic source classification, and ML model integration for advanced analytical and operational use cases.</div></li></ul></div><div><ul><li><div>
Mentor and grow a high-performing team of architects, engineers, and analysts&mdash;fostering innovation, cross functional collaboration, and delivery excellence.</div></li></ul></div><div><ul><li><div>
Champion AI and data architecture as strategic enablers of business transformation&mdash;linking technology decisions directly to measurable client outcomes.</div></li><li><div>
Provide technical leadership within sales processes and client pursuits</div></li><li><div>
Identify and cultivate new opportunities within existing and prospective accounts</div></li></ul></div><div><p><b>
Technologies &amp; Concepts</b></p></div><div><ul><li><div>
Programming &amp; APIs: PySpark, Python, FastAPI, FastMCP, SQL, OAuth2</div></li></ul></div><div><ul><li><div>
GenAI &amp; Agentic Tools: RAGAS, Langfuse, LangGraph, Llamaindex, Vector Databases (FAISS, PGVector, Weaviate, AWS Bedrock, Azure AI Search)</div></li></ul></div><div><ul><li><div>
AI Architectures: Retrieval-Augmented Generation, In-Context Learning, Agent Design, Function Calling, LLM Fine-Tuning &amp; Adaptation Strategies</div></li></ul></div><div><ul><li><div>
Data Engineering: Real-time ingestion pipelines, transformation logic, schema evolution, semi-structured data workflows</div></li></ul></div><div><ul><li><div>
Data Analytics &amp; Quality: Exploratory Data Analysis, advanced classification, data quality reporting and observability</div></li></ul></div><div><ul><li><div>
Enterprise Integration: Secure API architecture, user feedback loops, instrumentation with Langfuse for traceability, MLOps and LLMOps frameworks to operationalise and govern ML/LLM pipelines across environments</div></li></ul></div><div><p><b>
Your Profile</b></p></div><div><ul><li><div>
Proven experience designing and scaling GenAI-enabled and data-driven architectures.</div></li></ul></div><div><ul><li><div>
Strong grounding in software engineering principles and AI/ML enablement.</div></li></ul></div></div><div><div><ul><li><div>
Demonstrated ability to lead, mentor, and grow cross-functional technical teams.</div></li></ul></div><div><ul><li><div>
Track record of delivering innovative, scalable solutions that drive clear business value.</div></li><div></div><li><div><br>
Experience influencing CXO-level stakeholders</div></li><li><div>
Strong commercial mindset linking architecture to business value</div></li></ul></div><div></div><div><ul><li><div><br>
Exceptional communication skills.</div></li></ul></div><div><ul><li><div>
Passion for shaping intelligent systems and applying emerging technologies to solve real-world challenges.</div></li></ul></div></div><div></div><div><div><b><br>
Why Join?</b></div></div><div></div><div><ul><li><div><br>
Strategic Impact &ndash; Shape the commercial growth engine of one of Kearney&rsquo;s fastest-growing digital businesses.</div></li></ul></div><div><ul><li><div>
Collaborative Ecosystem &ndash; Work with top technology partners and world-class consulting teams.</div></li></ul></div><div><ul><li><div>
Growth &amp; Development &ndash; Access Kearney&rsquo;s global learning programs and partner certifications.</div></li></ul></div><div><ul><li><div>
Culture &ndash; Join a hands-on, high-energy, and inclusive environment focused on innovation and impact.</div></li></ul></div><div><ul><li><div>
Purpose &ndash; Help global enterprises unlock value through trusted data foundations, AI enablement, and digital transformation.</div></li></ul></div><div></div><div><div><b><br>
Equal Employment Opportunity and Non-discrimination</b></div></div><div><p>
Kearney Activate prides itself on providing a culture that allows employees to bring their best selves to work every day. Our people can feel comfortable, confident, and joyful to do great things for our firm, our teams, and our clients. Kearney Activate aims to build diverse capabilities to help our clients solve their most mission critical problems. Kearney Activate is committed to building a diverse, unbiased and inclusive workforce. Kearney Activate is an equal opportunity employer; we recruit, hire, train, promote, develop, and provide other conditions of employment without regard to a person&rsquo;s gender identity or expression, sexual orientation, race, religion, age, national origin, disability, marital status, pregnancy status, veteran status, genetic information or any other differences consistent with applicable laws. This includes providing reasonable accommodation for disabilities, or religious beliefs and practices. Members of communities historically underrepresented in analytics and consulting are encouraged to apply.</p></div><p></p><h3 class="jobSectionHeader"><b>
Language Requirements</b></h3><p>
Arabic and English</p></div>

Data and AI Solution Architect

<div><div>This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.</div><div></div><div><b><br>
&quot;DDN's A3I solutions are transforming the landscape of AI infrastructure.&quot; &ndash; IDC</b></div><div></div><div><b><i><br>
&ldquo;The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments&rdquo; - Marc Hamilton, VP, Solutions Architecture &amp; Engineering | NVIDIA</i></b></div><div></div><div><br>
DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence.</div><div></div><div><br>
Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management.</div><div></div><div><br>
Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage.</div><div><br>
DDN is seeking a highly experienced Senior Staff Engineer specializing in AI Data Path &amp; Storage to lead hands-on development and integration of advanced storage systems with next-generation AI inference pipelines. This role involves coding, prototyping, and rapidly iterating on solutions in close collaboration with architects to design and deliver high-performance data movement architectures. You will leverage NVIDIA&rsquo;s NIXL (Inference Transfer Library) alongside the Infinia Data Intelligence Platform to enable ultra-low-latency, high-throughput data movement across GPU, memory, and distributed storage layers, including workloads involving KV cache management and vector database retrieval. The ideal candidate brings deep expertise in distributed storage, GPU data paths, and large-scale system optimization, with a proven track record of building and shipping production-grade AI infrastructure.</div><div></div><div><br>
Key Responsibilities</div><ul><li>
Lead the design and implementation of high-performance data movement pipelines using NVIDIA NIXL across GPU, CPU, and storage tiers.</li><li>
Architect and drive integration of DDN Infinia with GPU-accelerated inference platforms for large-scale, real-time AI workloads.</li><li>
Own end-to-end optimization of I/O paths between GPU memory and storage using technologies such as NVIDIA GPUDirect Storage, RDMA, and NVMe-over-Fabrics.</li><li>
Define and implement multi-tier storage architectures (NVMe, SSD, object storage) optimized for inference latency, throughput, and scalability.</li><li>
Lead development of advanced KV cache management strategies, including offloading, prefetching, and persistence across distributed storage layers.</li><li>
Partner with AI/ML engineering teams to optimize inference performance in frameworks such as PyTorch and TensorFlow.</li><li>
Establish benchmarking frameworks and lead performance tuning efforts for storage and data movement in production inference environments.</li><li>
Diagnose and resolve complex system bottlenecks across storage, networking, and GPU subsystems.</li><li>
Influence architecture decisions for distributed inference systems, ensuring scalability, resilience, and efficient data locality.</li><li>
Drive engineering excellence through best practices in observability, performance monitoring, automation, and reliability engineering.</li><li>
Mentor junior engineers and provide technical leadership across cross-functional teams.</li></ul><div></div><div><br>
Required Qualifications</div><ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or a related field.</li><li>
12+ years of experience in storage systems, distributed systems, or performance engineering.</li><li>
Proven track record of architecting and delivering large-scale, high-performance infrastructure systems.</li><li>
Deep expertise in distributed storage architectures (object storage, scalable file systems, or cloud-native storage platforms).</li><li>
Strong understanding of Linux I/O stack, filesystem internals, and storage protocols.</li><li>
Extensive hands-on experience with NVMe, SSD optimization, and high-performance storage environments.</li><li>
Strong experience with RDMA, InfiniBand, or other high-speed data transfer technologies.</li><li>
Solid understanding of GPU computing concepts and CPU&ndash;GPU data movement patterns.</li><li>
Proficiency in Python and/or C/C++, with advanced debugging, profiling, and performance tuning skills.</li><li>
Demonstrated ability to optimize latency-sensitive, high-throughput production systems.</li></ul><div></div><div><br>
Preferred Skills</div><ul><li>
Hands-on experience with NVIDIA NIXL or similar data movement frameworks.</li><li>
Experience with GPU-aware storage pipelines and GPUDirect Storage.</li><li>
Strong understanding of AI inference systems, LLM serving architectures, and KV cache optimization.</li><li>
Experience with Retrieval-Augmented Generation (RAG) pipelines and open vector search ecosystems.</li><li>
Background in high-performance computing (HPC) or hyperscale distributed environments.</li><li>
Expertise in caching strategies, memory tiering, and data locality optimization.</li><li>
Experience designing disaggregated compute and storage architectures.</li></ul><div></div><div><br>
What You&rsquo;ll Work On</div><ul><li>
Leading the evolution of storage systems into GPU-native data layers for AI inference</li><li>
Building next-generation distributed AI infrastructure using NIXL and Infinia</li><li>
Driving performance breakthroughs in real-time LLM inference at scale</li><li>
Designing storage architectures for large-scale AI datasets and retrieval systems</li></ul><p><br>
Join our dynamic and driven team, where engineering excellence is at the heart of everything we do. We seek individuals who love to challenge themselves and are fueled by curiosity. Here, you'll have the opportunity to work across various areas of the company, thanks to our flat organizational structure that encourages hands-on involvement and direct contributions to our mission. Leadership is earned by those who take initiative and consistently deliver outstanding results, both in their work ethic and deliverables, making strong prioritization skills essential. Additionally, we value strong communication skills in all our engineers and researchers, as they are crucial for the success of our teams and the company as a whole.</p><p></p><p><b><br>
Interview Process: </b>After submitting your application, one of our recruiters will review your resume. If your application passes this stage, you will be invited to a 30-minute interview during which a member of our team will ask some basic questions. If you clear the interview, you will enter the main process, which can consist of up to four interviews in total:</p><br>
<p></p><ul><li>
Coding assessment: Often in a language of your choice.</li><li>
Systems design: Translate high-level requirements into a scalable, fault-tolerant service (depending on role).</li><li>
Real-time problem-solving: Demonstrate practical skills in a live problem-solving session.</li><li>
Meet and greet with the wider team.</li><li>
Our goal is to finish the main process in 2-3 weeks at most.</li></ul><p></p><p><b><br>
DataDirect Networks (DDN) is an Equal Opportunity/Affirmative Action employer. </b>All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.</p><div></div><div><br>
#LI-Remote</div></div>

Senior Staff Engineer - AI Data Path

MA'ADEN

<div><p><b>About Maaden
</b></p><p>Maaden, established in 1997, is one of the fastest-growing mining companies in the world and the largest multi-commodity mining and metals company in the Middle East. We are leading the development of the mining industry to become the third pillar of Saudi Arabia&rsquo;s economy by building a world-class, unique, and fully integrated mining value chain. We are pleased to share an exciting opportunity for the below mentioned position. This role offers a chance to contribute to our ambitious growth and play a key part in shaping the future of mining in the Kingdom.
</p><p><b>Job purpose
</b></p><p>The Principal Specialist, Data Modeling &amp; Architecture (OT) is the architectural authority for modeling operational technology (OT) and industrial data, ensuring consistent representation of assets, events, measurements, and production contexts across plants, sites, and operational systems. The role enables trusted OT analytics by defining standard models that align historians, SCADA/DCS, condition monitoring, and maintenance data with enterprise IT data products.
</p><p>The position ensures OT constraints&mdash;such as high-volume time-series data, latency requirements, site variability, and intermittent connectivity&mdash;are addressed through practical modeling patterns, semantic consistency, and governance-by-design across OT-to-IT integration.
</p><p><b>Key Accountabilities
</b></p><div><ul><li>Define OT data modeling standards for time-series, events, alarms, and asset hierarchies to support operational analytics and reliability use cases.
</li></ul><ul><li>Establish canonical OT concepts (asset, tag, measurement, work order linkage, location hierarchy) and ensure consistent adoption across sites and solutions.
</li></ul><ul><li>Architect OT-to-IT data alignment patterns that map operational measurements to enterprise entities for cross-domain reporting and performance analysis.
</li></ul><ul><li>Ensure OT models account for historian characteristics (high frequency, compression, interpolation, quality flags) and streaming ingestion patterns.
</li></ul><ul><li>Design scalable schemas for curated OT layers and OT data products, including auditability, lineage, and quality attributes.
</li></ul><ul><li>Partner with OT engineering, cyber/security, and platform teams to ensure secure, segmented, and compliant design for OT data flows.
</li></ul><ul><li>Review OT data solution designs and vendor deliverables; provide design authority to resolve modeling trade-offs and ensure long-term maintainability.
</li></ul><ul><li>Define reusable patterns for site onboarding and variability handling (naming normalization, tag mapping, unit standardization, reference data).
</li></ul>Coach engineers and modelers on OT semantics and modeling best practices; lead design reviews for critical OT initiatives.<br>
<ul><li>
</li></ul></div><p></p><p><b>Minimum Qualification, Experience and Competencies
</b></p><p><b>Minimum Qualification
</b></p><ul><li>Bachelor&rsquo;s degree in Computer Science/Engineering, Industrial Engineering, Data Engineering, or related field.
</li><li>Master&rsquo;s degree preferred; OT/industrial systems background is an advantage.
</li></ul><p><b>Minimum Experience
</b></p><ul><li>10&ndash;15 years of experience in data modeling/architecture with demonstrated exposure to OT/industrial data landscapes.
</li><li>Experience working with historians, industrial protocols/systems, and integrating OT data into enterprise analytics platforms.
</li></ul><p><b>Maaden High Performance Competencies
</b></p><ul><li>Strategic Thinking &amp; Decision Making &ndash; Anticipates implications and guides enterprise direction.
</li><li>Collaboration &amp; Influencing &ndash; Aligns diverse stakeholders without direct authority.
</li><li>Execution Excellence &ndash; Sets high standards and ensures measurable outcomes.
</li><li>Innovation &amp; Adaptability &ndash; Applies modern practices and evolves standards pragmatically.
</li><li>Change Leadership &ndash; Drives adoption, governance, and continuous improvement.
</li></ul><p><b>Skills
</b></p><ul><li>Deep understanding of OT data characteristics (time-series, events, alarms, quality flags) and asset hierarchies.
</li><li>Ability to model and integrate OT and IT data for enterprise analytics and operational performance reporting.
</li><li>Knowledge of SCADA/DCS/historians, sensors, and industrial context; familiarity with reliability/maintenance data linkages.
</li><li>Strong governance-by-design mindset including classification, access control, and auditability for industrial data.
</li><li>Stakeholder engagement across plant/site operations, OT engineering, IT, and data platform teams.</li></ul></div>

Principal Specialist, Data Modeling & Arch (OT)

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