planning engineer

estimation engineer

engineering manager

project engineer

design engineer

data engineer

Capgemini

<div><div><div><div><div><div><div><h2 class="jobSectionHeader"><b>About the job you are considering</b></h2>
</div><div><p>Capgemini Global Insights &amp; Data business line is a market leader in the data, platform, and analytics across all regions and across many sectors (including financial services, consumer products, manufacturing &amp; life sciences). Our offerings include end-2-end data integration to cloud platform, complete suite of AI engineering capabilities and a category of sector-based advanced analytics / AI solutions.</p>
<p>The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Your Role</b></h2>
</div><div><p>We are seeking an experienced and visionary Lead Data Engineer (Cloud) to lead our data-driven decision-making processes. This role requires someone with a balance of analytical skills, strategic foresight, and the ability to collaborate effectively across diverse teams. The Data Engineer will be instrumental in creating scalable data pipelines, optimizing data architectures, and ensuring the overall security and reliability of cloud-based data solutions. The ideal candidate will have a strong background in data architecture, ETL pipelines, cloud platforms (AWS, Azure, GCP), and big data technologies.</p><br>
<p></p><ul><li>Design, develop, and maintain scalable ETL (Extract, Transform, Load) pipelines using cloud-native tools.</li>
<li>Implement best practices for data ingestion, transformation, and loading processes across multiple sources.</li>
<li>Automate workflows and develop data pipelines using tools such as Apache Airflow, Glue, Databricks, or Dataflow.Architect, build, and maintain cloud-based data solutions using AWS, Azure, or Google Cloud Platform (GCP).</li>
<li>Optimize cloud infrastructure for cost, performance, and security.</li>
<li>Implement monitoring, logging, and alerting solutions for data pipelines and cloud infrastructure.</li>
<li>Bachelor's degree in data science, Analytics, Business, or related field. Advanced degrees or certifications are a plus.</li>
</ul></div></div><div><div><h2 class="jobSectionHeader"><b>Your Skills and Experience</b></h2>
</div><div><ul><li>Analytical Thinking &amp; Problem Solving: Proven ability to dissect complex problems and provide actionable insights in a timely manner.</li>
<li>Proficiency with cloud platforms such as AWS (S3, EC2, EMR, Glue, Lambda), Azure (Data Factory, Blob Storage, HDInsight), or GCP (Big Query, Dataflow, Pub/Sub).</li>
<li>Strong programming skills in Python, Java, Scala, or SQL.</li>
<li>Experience with big data tools (Hadoop, Spark, Kafka, etc.).</li>
<li>Proficiency with ETL processes and data transformation techniques.</li>
<li>Knowledge of relational and different databases (PostgreSQL, MongoDB, Cassandra).</li>
</ul></div></div><div><div><h2 class="jobSectionHeader"><b>Why you should consider Capgemini</b></h2>
</div><div><p>Growing clients&rsquo; businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you&rsquo;ll join a thriving company and become part of a diverse collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what&rsquo;s possible. It&rsquo;s why, together, we seek out opportunities that will transform the world&rsquo;s leading businesses, and it&rsquo;s how you&rsquo;ll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you&rsquo;ll build the skills you want. You&rsquo;ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>About Capgemini</b></h2>
</div><div><p>Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of &euro;22.5 billion. Make it real | www.capgemini.com</p></div></div></div></div></div></div></div>

Lead Data Engineer

GenBio AI

<div>
 GenBio AI develops multiscale foundation models to decode and simulate human biology. Our team is accelerating towards an ambitious future where scientists can unlock humanity's biggest challenges in drug discovery, healthcare, and fundamental research with AIDO (AI-Driven Digital Organism): a unified framework for predicting, simulating, and programming biology across all scales. The foundation of this vision begins today as we engineer the virtual cell to model and simulate the fundamental unit of life.
 <br/>
 <br/>
 This vision has brought together a talent-dense group of product-minded researchers and engineers dedicated to bringing it to reality. Our team prides itself on our strong engineering culture and highly interdisciplinary and collaborative approach. We are based in Palo Alto, with satellite offices in Paris and Abu Dhabi.
 <br/>
 <br/>
 As our data ingestion needs grow, we are looking for a Bioinformatics Data Engineer to act as the crucial bridge between raw biological data and our scalable infrastructure. Reporting to the Data Engineering Lead, you will leverage your deep biological domain expertise to build the initial scripts and processing logic for complex datasets, ensuring they are primed for large-scale foundation model training.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Source &amp; Acquire Biological Data - Identify, evaluate, and obtain high-quality bioinformatics datasets from public and partner sources (e.g., NCBI, PubChem, ENCODE,UniProt etc.) to support research and model development initiatives
  </li>
  <li>
   Deeply Understand Complex Datasets - Develop a comprehensive understanding of biological datasets, including data structures, schemas, metadata standards, entity relationships, and underlying biological context to ensure accurate interpretation and usage
  </li>
  <li>
   Design &amp; Implement Data Processing Pipelines - Develop robust preprocessing scripts and scalable data transformation workflows using Python, R, and relevant Tools. Leverage AI-assisted tools where appropriate to process, clean, normalize, and integrate complex biological data for foundation model training
  </li>
  <li>
   Structure &amp; Standardize Biological Data - Organize heterogeneous datasets into well-defined, interoperable formats aligned with internal infrastructure requirements and downstream AI training pipelines
  </li>
  <li>
   Bioinformatics Data Analysis - Perform exploratory and statistical analysis of genomic, transcriptomic, proteomic, and other multi-omics datasets to assess data quality, uncover biological patterns, and generate insights that inform model development. Apply appropriate computational and statistical methods to validate assumptions and support downstream AI training and evaluation
  </li>
  <li>
   Build Data Products - Create production-ready data assets, including standardized datasets, curated releases, dashboards, analytical reports, and technical documentation to enable efficient research and model evaluation
  </li>
  <li>
   Ensure Data Quality &amp; FAIR Compliance - Curate, annotate, validate, and standardize public and partner datasets in alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles, ensuring long-term usability and reproducibility
  </li>
  <li>
   Collaborate Cross-Functionally - Partner closely with research scientists and ML engineers to translate biological research needs into scalable data engineering solutions that support AI model training and evaluation
  </li>
  <li>
   Knowledge Sharing &amp; Documentation - Contribute domain expertise by documenting data methodologies, maintaining clear technical documentation, and sharing biological data insights across teams
   <br/>
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Educational Background: Bachelor&rsquo;s or Master&rsquo;s degree in Bioinformatics, Computational Biology, Computer Science, or a related field with a heavy focus on the life sciences
  </li>
  <li>
   Biological Data: Deep, hands-on familiarity with multiple biomedical data modalities (e.g., genomics, transcriptomics, spatial omics, protein structure, biomedical imaging, clinical/phenotypic data, etc.)
  </li>
  <li>
   Biological Tools: Familiar with Bioconda,Biopython,Bioconductor, samtools,bamtools,bcftools,gffutils etc
  </li>
  <li>
   Scripting &amp; Tooling: Strong programming skills in Python (Pandas, NumPy) and proficiency with standard bioinformatics workflow managers and tools (e.g., Ray, Kubeflow)
  </li>
  <li>
   Engineering Handoff: Experience writing clean, modular code that can be easily picked up by core data engineers for optimization in cloud environments (AWS/GCP/HF) and containerized setups (Docker)
  </li>
  <li>
   AI/ML Awareness: A solid understanding of machine learning workflows and how biological data must be formatted and batched for deep learning frameworks (e.g., PyTorch)
   <br/>
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 Join us as we embark on this journey to redefine the future of biology and medicine.
 <br/>
 <br/>
 We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. GenBio AI participates in the U.S. Department of Homeland Security&rsquo;s E-Verify program to confirm the employment eligibility of all newly hired employees. For more information on E-Verify, please visit www.e-verify.gov.
 <br/>
 <br/>
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>


Bioinformatics Data Engineer

DXC Technology

<div>
 <p>
  <strong>
   Databricks Data Platform Engineer/Architect
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Project description
  </strong>
 </p>
 <p>
  We are seeking a highly skilled Databricks Platform Engineer with strong experience in data engineering. The candidate will have a deep understanding of both data platforms and software engineering, enabling them to effectively integrate and operate the platform within a broader IT ecosystem.
 </p>
 <p>
  This role requires a hands-on individual contributor who takes full ownership of deliverables end-to-end, including design, development, testing, deployment, and ongoing support.
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Manage and optimize Databricks data platform including workspace setup, cluster policies, job orchestration, Unity Catalog, cost controls, multi-tenancy.
  </li>
  <li>
   Design, write and maintain APIs used for Platform automation, Serverless workflows, Deployment pipelines, release management and repository management
  </li>
  <li>
   Ensure high availability, security, and performance of data systems which includes access control, secrets management, RBAC, monitoring, alerting, RLS, incident handling, performance tuning.
  </li>
  <li>
   Provide valuable insights about the data platform (Databricks) usage which includes cost attribution, usage analytics, workload patterns, telemetry.
  </li>
  <li>
   Implementing new features of Databricks, including serverless, Declarative Pipelines, Agents, lakebase , etc.
  </li>
  <li>
   Design and maintain system libraries (Python) used in ETL pipelines and platform governance (Databricks).
  </li>
  <li>
   Optimize ETL Processes
  </li>
  <li>
   Enhance and tune existing ETL processes for better performance, scalability, and reliability.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Skills
  </strong>
 </p>
 <p>
  <strong>
   Must have
  </strong>
 </p>
 <ul>
  <li>
   Minimum 10 Years of experience in IT/Data.
  </li>
  <li>
   Minimum 5 years of experience as a Databricks Data Platform Engineer.
  </li>
  <li>
   3+ years of experience in designing, writing, and maintaining APIs used for Platform automation, Serverless workflows, Deployment pipelines, release management and repository management
  </li>
  <li>
   Bachelor's in IT or related field.
  </li>
  <li>
   Infrastructure &amp; Cloud: Azure, AWS (expertise in storage, networking, compute).
  </li>
  <li>
   Programming: Proficiency in PySpark for distributed computing.
  </li>
  <li>
   minimum 4 years of Python experience for ETL development.
  </li>
  <li>
   SQL: Expertise in writing and optimizing SQL queries, preferably with experience in databases such as PostgreSQL, MySQL, Oracle, or Snowflake.
  </li>
  <li>
   Data Warehousing: Experience working with data warehousing concepts and Databricks platform.
  </li>
  <li>
   ETL Tools: Familiarity with ETL tools &amp; processes
  </li>
  <li>
   Data Modelling: Experience with dimensional modelling, normalization/denormalization, and schema design.
  </li>
  <li>
   Version Control: Proficiency with version control tools like Git to manage codebases and collaborate on development.
  </li>
  <li>
   Data Pipeline Monitoring: Familiarity with monitoring tools (e.g., Prometheus, Grafana, or custom monitoring scripts) to track pipeline performance.
  </li>
  <li>
   Data Quality Tools: Experience implementing data validation, cleaning, and quality frameworks, ideally Monte Carlo.
  </li>
 </ul>
 <p>
  <strong>
   Nice to have
  </strong>
 </p>
 <ul>
  <li>
   Containerization &amp; Orchestration: Docker, Kubernetes.
  </li>
  <li>
   Infrastructure as Code (IaC): Terraform.
  </li>
  <li>
   Understanding of Investment Data domain (desired).
  </li>
 </ul>
</div>


Databricks Data Platform Engineer/Architect

Faze 3 Consulting

<p><b>AI Data UX Engineer</b></p><p><b>Design and ship the human side of enterprise AI.</b></p><p>A leading Abu Dhabi-based holding group is hiring an <b>AI Data UX Engineer</b> to design and build the user experience layer for AI assistants, BI surfaces, and data apps across desktop, mobile, and Teams. If you can both design <i>and</i> ship production frontends &mdash; and you care about making complex data genuinely usable &mdash; we want to hear from you. Reports to the AI Solutions Manager.</p><p><b>What you'll own:</b></p><ul><li>Translate business workflows into wireframes, prototypes, and tested UI patterns in Figma and Fluent UI.</li><li>Implement production-grade frontends using React, TypeScript, Power Apps, and Power Pages, integrated with AI and REST APIs.</li><li>Design Power BI experiences &mdash; reports, semantic models, and themes &mdash; optimized for decisions and performance.</li><li>Instrument telemetry, A/B tests, and in-app guidance; iterate based on usage analytics.</li><li>Ensure accessibility (WCAG 2.1 AA), localization, and secure-by-design patterns (MSAL, role-based UI).</li><li>Collaborate with the delivery partner's squads and internal engineers to align UX with platform constraints and non-functionals &mdash; making data availability a first-class design and delivery outcome.</li><li>Enable in-app data querying, guided data correction flows, and user feedback loops to improve data discoverability and quality.</li><li>Partner with Data Ops and platform teams for backend implementation of data write-back patterns; ensure UX patterns respect RBAC, logging, and governance controls.</li><li>Integrate robust CRUD operations and database interactions so users can efficiently access, manage, and update information.</li><li>Design governed user experiences for data interaction &mdash; search, view, update requests, approvals &mdash; aligned to access controls, auditability, and workflow patterns, without owning core database engineering.</li><li>Design explainability and trust UX: citations, confidence cues, audit trails, and &quot;why this answer&quot; patterns for assistants and analytics surfaces to improve adoption and responsible use.</li><li>Work closely with the delivery partner's visualization and UX engineers on a shared &quot;definition of done&quot; for dashboards, assistant UX surfaces, and adoption telemetry.</li></ul><p><b>What you bring</b></p><ul><li>4&ndash;6 years in product or UX engineering for data/AI products.</li><li>A portfolio demonstrating shipped enterprise experiences across web, mobile, Teams, or Power Platform.</li><li>Bachelor's in Design, Computer Science, Information Systems, or equivalent portfolio-based experience.</li></ul><p><b>Core skills and tools</b></p><ul><li>Figma, Fluent UI, React/TypeScript, HTML/CSS.</li><li>Power Apps and Power Pages; MSAL and Microsoft Graph integration.</li><li>Power BI: DAX, modeling, performance tuning, governance with Fabric/Purview.</li><li>UX research, usability testing, accessibility, localization, and content design.</li><li>Telemetry (App Insights), feature flags, and experimentation.</li></ul><p><b>Preferred certifications</b></p><ul><li>Microsoft Certified: Power Platform App Maker (PL-100) or Developer (PL-400).</li><li>Microsoft Certified: Power BI Data Analyst Associate (PL-300).</li><li>Any recognized UX/HCI certification.</li></ul><p><b>Location: </b>Abu Dhabi, UAE</p><p><b>Employment Type: </b>Full-time</p><p><b>Experience: </b>4-6 years</p><p><b>Salary Range: </b>12,000 - 18,000 (AED per month)</p><p>Pay: AED12,000.00 - AED18,000.00 per month</p><p>Work Location: In person</p>

AI Data UX Engineer

TAT IT Technolgies

<div>
 <strong>
  We have an Urgent requirement for Confluent Kafka Engineer with experience in real time data streaming for one of our banking client in Abu Dhabi, UAE
  <br/>
  <br/>
 </strong>
 <strong>
  Strong experience in Confluent Kafka is MUST for this role
  <br/>
  <br/>
 </strong>
 <strong>
  Design, develop, and maintain real-time data streaming solutions using Confluent Kafka&mdash;Must for this role
  <br/>
  <br/>
 </strong>
 <strong>
  Develop and manage Kafka producers, consumers, topics, partitions, and schemas&mdash;Must for this role
  <br/>
  <br/>
 </strong>
 <strong>
  Implement Kafka Streams, Kafka Connect, and integrations with external systems&mdash;-Must for this role
  <br/>
  <br/>
 </strong>
 <strong>
  Job Summary
  <br/>
  <br/>
 </strong>
 We are seeking a highly skilled Confluent Kafka Engineer to join our dynamic team. The ideal candidate will be responsible for the development, User Acceptance Testing (UAT), and production support of our Confluent Kafka-based systems. This role requires deep expertise in Kafka architecture, including Confluent Control Center, KSQLDB, Kafka Streams, and Kafka Connect. The engineer will collaborate closely with cross-functional teams to ensure the smooth operation of our data streaming services and provide support across various environments.
 <br/>
 <br/>
 <strong>
  Development
  <br/>
  <br/>
 </strong>
 <strong>
  Key Responsibilities:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, develop, and implement Kafka-based solutions to meet business requirements, utilizing Confluent Control Center, KSQLDB, Kafka Streams, and Kafka Connect.
  </li>
  <li>
   Write and maintain high-quality code for Kafka producers, consumers, and stream processing applications.
  </li>
  <li>
   Develop and manage Kafka connectors for seamless integration with external systems, ensuring data consistency and reliability.
  </li>
  <li>
   Utilize Kafka Streams for real-time processing of streaming data, transforming and enriching data as it flows through the pipeline.
  </li>
  <li>
   Employ KSQLDB for stream processing tasks, including real-time analytics and transformations.
  </li>
  <li>
   Collaborate with data engineers, software developers, and DevOps teams to integrate Kafka solutions with existing systems.
  </li>
  <li>
   Ensure all Kafka-based solutions are scalable, secure, and optimized for performance.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  User Acceptance Testing (UAT)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop and execute UAT plans to validate Kafka solutions, including components such as Kafka Streams, KSQLDB, and Kafka Connect, before deployment to production.
  </li>
  <li>
   Work closely with QA teams to identify and resolve defects during the UAT phase.
  </li>
  <li>
   Ensure all UAT activities comply with the organization&rsquo;s standards and best practices.
  </li>
  <li>
   Provide detailed reports on UAT outcomes and work with developers to implement necessary fixes.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Production Support
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Monitor and maintain Kafka clusters, including components like Confluent Control Center, to ensure high availability and reliability of data streaming services.
  </li>
  <li>
   Troubleshoot and resolve issues related to Kafka performance, latency, and data integrity, including issues specific to Kafka Streams, KSQLDB, and Kafka Connect.
  </li>
  <li>
   Perform routine maintenance tasks such as patching, upgrades, and backups for Kafka clusters and associated components.
  </li>
  <li>
   Implement monitoring solutions to proactively identify and mitigate potential production issues, leveraging Confluent Control Center for comprehensive cluster visibility.
  </li>
  <li>
   Provide 24/7 support for production systems, including participation in on-call rotation.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 Education: Bachelor&rsquo;s degree in Computer Science, Information Technology, or a related field.
 <br/>
 <br/>
 <strong>
  Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3+ years of hands-on experience with Apache Kafka and Confluent Kafka in a production environment, including experience with Confluent Control Center, KSQLDB, Kafka Streams, and Kafka Connect.
  </li>
  <li>
   Proven experience in Kafka development, including producer and consumer API, stream processing, and connector development.
  </li>
  <li>
   Experience with Kafka cluster management, including setup, configuration, monitoring, and troubleshooting.
  </li>
  <li>
   Familiarity with distributed systems, microservices architecture, and event-driven design patterns.
  </li>
  <li>
   Experience with cloud platforms (e.g., AWS, Azure) and containerization (Kubernetes) is a plus.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technical Skills
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proficiency in programming languages such as Java, Python, or Scala.
  </li>
  <li>
   Strong knowledge of Kafka internals, including brokers, zookeepers, topics, partitions, and offsets.
  </li>
  <li>
   Experience with monitoring tools (e.g., Prometheus, Grafana) and logging frameworks (e.g., Log4j, ELK Stack).
  </li>
  <li>
   Proficiency in using Confluent Control Center for monitoring, managing, and optimizing Kafka clusters.
  </li>
  <li>
   Expertise in Kafka Streams for building scalable, fault-tolerant stream processing applications.
  </li>
  <li>
   Experience with KSQLDB for real-time processing and analytics on Kafka topics.
  </li>
  <li>
   Strong understanding of Kafka Connect for integrating Kafka with external data sources and sinks.
  </li>
  <li>
   Understanding of networking, security, and compliance aspects related to Kafka.
  </li>
  <li>
   Familiarity with CI/CD pipelines and automation tools (e.g., Jenkins, GitLab CI).
   <br/>
   <br/>
  </li>
 </ul>
 Skills: bank,streams,kafka,confluent
</div>


Confluent Kafka Engineer-Bank

Siemens

<div><div><b>Job Title: Marketing Operations &amp; Data Specialist</b></div><br>
<div></div>
<div><b>You'll make a difference by:</b></div>
<ul><li><b>Architecting Intelligent Workflows:</b> Designing and managing end-to-end automation using Microsoft Power Automate, n8n, and RPA platforms like UiPath to streamline global marketing operations.</li>
<li><b>Turning Data into Strategy:</b> Integrating Snowflake and Power BI to engineer data pipelines and create high-impact visualizations that drive campaign decisions.</li>
<li><b>Scaling Content with AI:</b> Leading the charge on generative AI integration to revolutionize how the team creates, distributes, and localizes content across global channels.</li>
<li><b>Bridging Global Gaps:</b> Collaborating with international teams to identify process pain points, establishing best-practice frameworks, and centralizing media assets with consistent metadata.</li>
<li><b>Ensuring Technical Integrity:</b> Building scalable, secure integrations via APIs and Python/JavaScript scripting while maintaining rigorous cybersecurity and version control standards.</li>
<li><b>Optimizing the User Experience:</b> Analyzing campaign effectiveness through custom dashboards and refined UI/UX interfaces to present clear insights to stakeholders.</li></ul><br>
<div>
</div><div><b>Your defining qualities:</b></div>
<ul><li><b>Proven Track Record:</b> You bring 2&ndash;5 years of professional experience in marketing operations, data science, or a highly technical marketing role.</li>
<li><b>A Technical Polymath:</b> You have a solid background in Data Science, CS, or Marketing Informatics, with deep expertise in at least one core area (Automation, AI, or Data Management).</li>
<li><b>A MarTech Architect:</b> You have hands-on experience building complex workflows and integrating third-party tools into a cohesive marketing tech stack.</li>
<li><b>A Data Fluent Strategist:</b> You are proficient in ETL processes and modern data environments like Snowflake, with the ability to translate &quot;big data&quot; into &quot;big ideas.&quot;</li>
<li><b>An AI Pioneer:</b> You stay ahead of the curve with AI/ML models, generative AI, and prompt engineering to keep the business at the cutting edge.</li>
<li><b>A Cross-Functional Communicator:</b> You can translate complex technical concepts for non-technical stakeholders and thrive in multicultural, global environments.</li>
<li><b>A Creative Problem-Solver:</b> You are a solutions-oriented thinker who isn&rsquo;t afraid to challenge conventional methods and propose innovative improvements.</li></ul><div><br>
</div><b>
How to apply:</b><div><ul><li>
Applicable to all applicants, to be considered, please upload or share a portfolio of your previous work (PDF or link) along with your resume.</li><li>
Interested Siemens Internal candidates, kindly reach out directly to the respective in-country Talent Acquisition representative to initiate the application process instead.</li></ul><div><b>
This is what happens after you apply:</b></div>
<div></div><ul><li>CV Screening</li><li>
Talk with our recruiter to get to know your motivation &amp; your experience</li><li>
2-3 Business Interviews</li><li>
Offer</li></ul><br>
<div></div>
<div><b>Transform the everyday with us.</b></div>
<div>We value your unique identity and perspective and are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society. Come bring your authentic self and create a better tomorrow with us.</div><br>
<div></div>
<div><b>Public Notice: Recruitment Fraud</b></div>
<div>We wish to caution jobseekers that Siemens, as a policy, does not authorize external parties/agents to conduct employment drives or extend Offers of Employment on our behalf. We do not ask for bank details, payment of any kind nor personal financial information in return for assurance of employment. Please visit our job portal for all Siemens job openings, and apply via the portal.</div></div></div>

Marketing Operations & Data Specialist

TAQA Distribution

<div>
 <p>
  We are building a strong pipeline of
  <strong>
   IT &amp; Digital professionals
  </strong>
  to support upcoming initiatives and transformation programs.
 </p>
 <p>
  This is not for a specific vacancy, but an opportunity to
  <strong>
   join our talent pool
  </strong>
  and be considered for future roles aligned with your experience.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are interested in professionals across:
 </p>
 <ul>
  <li>
   Data &amp; AI (Data Science, Data Engineering, Data Governance, Architecture)
  </li>
  <li>
   Cloud, Infrastructure &amp; Enterprise Architecture
  </li>
  <li>
   Cybersecurity &amp; IT Risk
  </li>
  <li>
   Digital Transformation &amp; Innovation
  </li>
  <li>
   Applications, Software &amp; Platform Engineering
  </li>
  <li>
   IT Business Analysis &amp; Enterprise Solutions
  </li>
  <li>
   Project Management, PMO &amp; Service Delivery
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Who Should Apply
 </p>
 <ul>
  <li>
   IT &amp; Digital professionals with a
   <strong>
    minimum of 4+ years
   </strong>
   of relevant experience
  </li>
  <li>
   Candidates open to exploring future career opportunities
  </li>
  <li>
   Professionals seeking to contribute to high-impact, enterprise-level technology and digital transformation initiatives
  </li>
  <li>
   Experience at Associate, Senior, or equivalent levels is preferred
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What Happens Next
  </strong>
 </p>
 <ul>
  <li>
   Your profile will be reviewed and added to our talent pool
  </li>
  <li>
   We will reach out when a suitable opportunity becomes available
  </li>
 </ul>
 <p>
 </p>
</div>


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