civil engineer

project engineer

electrical engineer

planning engineer

electrical design engineer

data engineer

Edenred

<div><p>Take a step forward and let Edenred surprise you.
</p><p>Every day, we deliver innovative solutions to improve the life of millions of people, connecting employees, companies, and merchants all around the world.
</p><p>We know there are hundred ways for you to grow. With us, you will expand your skills in a multicultural, challenging, and dynamic environment.
</p><p></p><p><b>Dare to join Edenred and get ready to thrive in a global company that will offer you endless opportunities.
</b></p><p></p><p>Edenred is all about meritocracy. You come as you are, and you contribute. Indeed, the Edenred Group recognizes, recruits and develops all talents and singularities.
</p><p>We are committed to preventing all forms of discrimination and to providing all our candidates with equal opportunities regardless of their gender and gender expression, disability, origin, religious belief and sexual orientation or any other criteria.
</p><p></p><ul><li>The Role
</li></ul><p></p><p>We&rsquo;re looking for a Data Engineer Lead to architect, build, and scale the next generation of our data platform from the ground up. This role is ideal for someone who thrives in highimpact‑ environments, enjoys solving complex technical challenges, and wants to shape the long‑term data strategy of a fast‑growing business. You&rsquo;ll work closely with engineering, product, analytics, and business teams to design modern data foundations that enable reliable insights, advanced analytics, and innovation across the organization. This is a unique opportunity to own the full lifecycle of our data ecosystem and influence how data powers decision‑making at scale.
</p><ul><li>Responsibilities
<br>
</li></ul><ul><li>Lead the end‑to‑end design, development, and scaling of a modern data platform on Azure and Databricks.
</li><li>Build, optimize, and maintain robust data pipelines and architectures supporting analytics, reporting, and advanced data products.
</li><li>Define and enforce best practices for data modeling, governance, quality, and security across all environments.
</li><li>Partner with cross‑functional teams to understand business needs and translate them into scalable technical solutions.
</li><li>Mentor and guide data engineers, fostering strong engineering standards, code quality, and operational excellence.
</li><li>Oversee platform performance, reliability, and cost efficiency, proactively identifying areas for improvement.
</li><li>Drive continuous innovation by evaluating new tools, technologies, and architectural approaches.
</li></ul><ul><li>YOUR PROFILE
 </li></ul><p></p><ul><li>7+ years of experience in data engineering, including at least 3 years in a senior or lead role.
</li><li>Proven experience designing and building a data platform from scratch in Azure and Databricks environments.
</li><li>Deep expertise in Azure Data Lake Storage, Databricks, Unity Catalog, Delta Lake, and Azure Data Factory (Certified Data Engineer by Azure/Certified Data Engineer Databricks is a plus)
</li><li>Strong proficiency in Python, PySpark, and SQL, with handson experience processing largescale datasets.
 </li><li>Solid understanding of data modeling, Medallion Architecture, and bestinclass data governance practices.
</li><li>Experience leading technical teams, setting engineering standards, and mentoring others.
</li><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Statistics,Mathematics, or a related field&mdash;or equivalent practical experience.
</li><li>A collaborative, proactive problemsolver with strong communication skills and the ability to work effectively across diverse teams.
</li></ul><ul><li>REPORTING STRUCTURE:
</li></ul><p></p><p>The selected candidate will report directly to the Data Manager who is responsible for ensuring that projects and applications are managed appropriately.
</p><ul><li>The Data Engineer Lead will work closely with engineering, product, IT, and business stakeholders to design and scale the data platform that underpins analytics, reporting, and advanced data products across the organization. This role requires strong partnership with data analysts, data scientists, and domain experts to ensure data solutions are aligned with business needs and deliver measurable impact. The selected candidate will report directly to the Data Manager and will play a key role in guiding technical decisions, influencing data strategy, and ensuring that data initiatives are executed effectively and collaboratively.
</li></ul><p></p><p><b>Apply now and Vibe with Us!</b></p></div><p></p>

Data Engineer Lead

GSSTech Group

<div><p>We are looking for a highly skilled Senior Data Engineer with strong expertise in PySpark, Python, and Big Data technologies to design, build, and optimize scalable data platforms and pipelines. The ideal candidate will work closely with Data Scientists, Business Analysts, and Analytics Delivery teams to develop high-performance analytics solutions and support advanced data science initiatives.</p><b><br>
Requirements</b><br>
<br>
Key Responsibilities<ul><li>
Collaborate with Analytics Delivery Leads and Lead Data Engineers to understand business requirements and deliver impactful data solutions.</li><li>
Work closely with Data Scientists and cross-functional teams to solve complex business problems through data engineering solutions.</li><li>
Manage data onboarding, data access, and stakeholder coordination for analytics initiatives.</li><li>
Design, develop, and maintain scalable, secure, and high-performance data pipelines.</li><li>
Acquire, ingest, process, and transform large-scale structured and unstructured datasets.</li><li>
Implement data engineering best practices for building reliable and production-ready data platforms.</li><li>
Perform data wrangling, cleansing, transformation, and feature engineering for machine learning and analytics use cases.</li><li>
Design and develop modular data pipelines to generate reusable features and modeling datasets.</li><li>
Build and optimize data architectures supporting advanced analytics and machine learning workloads.</li><li>
Contribute to data platform design by selecting appropriate technologies across Big Data, SQL, and NoSQL ecosystems.</li><li>
Ensure data quality, integrity, governance, security, and scalability across the data lifecycle.</li><li>
Participate in Agile squads and collaborate effectively with stakeholders across business and technology teams.</li><li>
Contribute to enterprise data architecture strategy and roadmap aligned with business objectives.</li></ul>
Required Technical SkillsCore Data Engineering<ul><li>
Strong experience in Data Engineering and Big Data solutions.</li><li>
Expert-level proficiency in PySpark.</li><li>
Strong programming experience in Python.</li><li>
Experience building large-scale distributed data processing pipelines.</li></ul>
Data Processing &amp; ETL<ul><li>
Data Ingestion</li><li>
Data Transformation</li><li>
Data Wrangling</li><li>
Data Preparation</li><li>
Data Modeling</li><li>
Feature Engineering</li><li>
ETL/ELT Development</li><li>
Batch Processing</li><li>
Data Pipeline Development</li></ul>
Big Data Technologies<ul><li>
Apache Spark / PySpark</li><li>
Distributed Data Processing Frameworks</li><li>
Big Data Ecosystems</li></ul>
Database Technologies<ul><li>
Strong SQL expertise</li><li>
Experience with Relational Databases</li><li>
Experience with NoSQL Databases</li><li>
Data Warehousing Concepts</li></ul>
Cloud &amp; Analytics Platforms (Preferred)<ul><li>
Azure Data Platform</li><li>
AWS Data Services</li><li>
Google Cloud Data Services</li><li>
Databricks</li><li>
Hadoop Ecosystem</li></ul>
Machine Learning Data Support<ul><li>
Feature Engineering for ML Models</li><li>
Data Preparation for Analytics and AI Use Cases</li><li>
Building Modeling and Feature Tables</li><li>
Supporting Data Science Workloads</li></ul>
Engineering Best Practices<ul><li>
Software Engineering Principles</li><li>
Data Pipeline Optimization</li><li>
Data Quality Management</li><li>
Performance Tuning</li><li>
Scalability &amp; Security</li><li>
Version Control (Git)</li><li>
CI/CD Concepts</li><li>
Documentation Standards</li></ul>
Required Soft Skills<ul><li>
Strong stakeholder management and communication skills.</li><li>
Experience working with Business Analysts, Data Scientists, and Product Teams.</li><li>
Ability to translate business requirements into scalable data solutions.</li><li>
Strong analytical and problem-solving skills.</li><li>
Experience working in Agile/Scrum environments.</li><li>
Ability to work independently and within cross-functional teams.</li></ul>
Preferred Qualifications<ul><li>
Experience working in enterprise-scale data platforms.</li><li>
Experience supporting machine learning and advanced analytics initiatives.</li><li>
Exposure to cloud-native data engineering solutions.</li><li>
Experience designing modern data architectures and data lake environments.</li></ul></div><p></p>

Senior Data Engineer

<div><p>We are looking for a highly skilled Data Engineer with strong expertise in PySpark and Informatica Platform Engineering to support enterprise-scale Digital Products and Digital Onboarding initiatives.</p><p>
The ideal candidate should have strong experience in enterprise data engineering, big data ecosystems, data architecture, and modern data management practices within large and complex environments, preferably in banking or financial services.</p><p></p><b><br>
Requirements</b><br>
<br>
Key Responsibilities<ul><li>
Design and develop scalable enterprise data engineering solutions using PySpark and Informatica platforms</li><li>
Build and model Raw Data Vault structures with strong understanding of:</li><li><ul><li>
Source system data structures</li><li>
Data retention policies</li><li>
Data partitioning strategies</li></ul></li><li>
Drive data reusability and reduce data duplication while optimizing performance</li><li>
Define and implement enterprise data architecture standards and best practices</li><li>
Create data exchange standards to support reusable and decoupled architectures</li><li>
Define standards for data archival, retention, and purging</li><li>
Identify and document critical data elements across enterprise source systems</li><li>
Collaborate with data engineers, architects, and source system SMEs to establish data engineering principles and governance standards</li><li>
Support large-scale data transformation and analytics initiatives</li><li>
Contribute to CI/CD-enabled data engineering and deployment environments</li><li>
Ensure compliance with enterprise data quality, governance, and security standards</li></ul>
Required Skills &amp; Experience<ul><li>
Strong hands-on experience in:</li><li><ul><li>
PySpark</li><li>
Informatica Platform Engineering</li><li>
Enterprise Data Engineering</li><li>
Big Data Ecosystems</li></ul></li><li>
Strong expertise in:</li><li><ul><li>
Data Architecture</li><li>
Data Strategy &amp; Roadmaps</li><li>
Enterprise Data Management</li><li>
Data Warehousing &amp; Analytics Solutions</li></ul></li><li>
Strong understanding of:</li><li><ul><li>
Dimensional Modeling</li><li>
Star &amp; Snowflake Schemas</li><li>
Slowly Changing Dimensions (SCD)</li><li>
Role-playing Dimensions</li><li>
Dimensional Hierarchies</li><li>
Data Classification</li></ul></li><li>
Experience transforming traditional Data Warehouse environments into Big Data-based architectures</li><li>
Expertise in:</li><li><ul><li>
Data Quality</li><li>
Data Profiling</li><li>
Data Governance</li><li>
Data Security</li><li>
Metadata Management</li><li>
Data Archival</li></ul></li><li>
Experience with cloud-native principles, architectures, and deployments</li><li>
Strong exposure to Continuous Integration (CI) and Continuous Deployment (CD) environments</li><li>
Strong analytical, troubleshooting, and problem-solving capabilities</li></ul>
Preferred Experience<ul><li>
Banking or financial services domain experience is highly preferred</li><li>
Experience working within enterprise-scale digital transformation programs</li><li>
Exposure to modern analytics and enterprise data platforms</li></ul>
Education<p>
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Information Systems, Information Technology, Engineering, or related field</p>
Preferred Candidate Profile<ul><li>
Ability to work in fast-paced and evolving environments</li><li>
Strong stakeholder collaboration and communication skills</li><li>
Experience handling multiple priorities and enterprise-scale projects</li><li>
Strong ownership mindset and attention to detail</li></ul></div>

Data Engineer - PySpark & Informatica

Tether Operations Limited

<div><p><b><i>Join Tether and Shape the Future of Digital Finance</i></b></p><p>
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.</p><p></p><p><b><i>
Innovate with Tether</i></b></p><p><b>
Tether Finance: </b>Our innovative product suite features the world&rsquo;s most trusted stablecoin, <b>USDT</b>, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.</p><p>
But that&rsquo;s just the beginning:</p><p><b>
Tether Power: </b>Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.</p><p><b>
Tether Data: </b>Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like <b>KEET</b>, our flagship app that redefines secure and private data sharing.</p><p><b>
Tether Education</b>: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.</p><p><b>
Tether Evolution</b>: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.</p><p></p><p><b><i>
Why Join Us?</i></b></p><p>
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.</p><p>
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.</p><p><b>
Are you ready to be part of the future?</b></p><p></p><p><b>
About the job</b></p><p>
We are developing a highly scalable media intelligence platform that processes, analyzes, and structures large volumes of multimedia content across text, image, video, and audio. As a Senior Applied ML Engineer, you will architect and build the core backend systems that power media ingestion, processing workflows, metadata generation, AI-based analysis, semantic search, and retrieval across large media libraries.</p><p>
We are looking for a Senior Applied ML Engineer who can design, implement, optimize, and evaluate a production-grade moderation pipeline using open-source models.</p><p></p><p>
This role requires deep backend engineering expertise, strong system design capability, and practical experience integrating AI/ML systems into production workflows. You will work on complex media-processing pipelines, video/audio analysis, OCR, speech-to-text, embedding generation, vector search, multimodal model integrations, and high-throughput asynchronous workloads. You will collaborate closely with engineering leadership to define backend architecture, improve reliability and scalability, and guide other engineers in delivering secure, observable, and high-performance systems.</p><p></p><p><b>
Responsibilities</b></p><p><b>
Backend Architecture &amp; System Ownership</b></p><ul><li>
Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems.</li><li>
Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration.</li><li>
Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows.</li><li>
Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.</li><li>
Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content.</li><li>
Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies.</li><li>
Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution.</li></ul><p><b>
AI/ML Integration &amp; Model Workflows</b></p><ul><li>
Lead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows.</li><li>
Integrate and optimize AI/ML services within backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies.</li><li>
Collaborate with ML engineers, data scientists, or external model providers to benchmark models, compare quality/latency trade-offs, and safely roll out model upgrades.</li></ul><p><b>
Model Serving &amp; Performance Optimization</b></p><ul><li>
Optimize AI/ML inference workflows for latency, throughput, reliability, and cost across both real-time and batch-processing paths.</li><li>
Work with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services to improve batching, concurrency, warmup behavior, timeout handling, autoscaling, and GPU utilization.</li><li>
Evaluate and apply practical model optimization techniques such as quantization, model distillation, batching, caching, prompt optimization, and routing to smaller or cheaper models where appropriate.</li><li>
Design and maintain vector search and indexing systems using technologies such as Pinecone, Weaviate, Qdrant, Elastic Vectors, FAISS, pgvector, or similar tools.</li><li>
Build retrieval workflows that support semantic search, similarity matching, duplicate detection, media discovery, and structured metadata search.</li><li>
Monitor model and system performance in production, including API latency, queue depth, processing time, model error rates, GPU utilization, confidence distributions, drift signals, and cost per processed item.Search, Indexing &amp; Data Retrieval</li></ul><p><b>
Infrastructure, Reliability &amp; Observability</b></p><ul><li>
Deploy and operate systems on AWS, GCP, Azure, or equivalent cloud platforms, including compute, storage, networking, queues, model-serving infrastructure, and monitoring systems.</li><li>
Ensure system reliability through logging, metrics, tracing, alerting, dashboards, operational runbooks, and incident-response best practices.</li></ul><p><b>
Collaboration &amp; Engineering Leadership</b></p><ul><li>
Collaborate with product, design, data, and ML teams to deliver media-rich, AI-powered product features.</li><li>
Mentor junior and mid-level engineers, support technical planning, review designs, and raise engineering quality across the team.</li><li>
Participate in code reviews, documentation, technical planning, and continuous improvement of engineering practices.</li><li>
Ensure code quality through testing, peer review, clear documentation, and maintainable implementation patterns.</li></ul><p><b><br>
Education &amp; Experience</b></p><ul><li>
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.</li><li>
5-7+ years of backend engineering experience, ideally building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services.</li><li>
Prior experience owning major backend modules end to end, including architecture, implementation, deployment, monitoring, and production operations.</li><li>
3 + years of experience integrating AI/ML inference systems into backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene detection, or multimodal model outputs.</li><li>
Hands-on experience creating AI-powered processing pipelines for image, video, audio, or text analysis.</li><li>
Practical experience with production model optimization, especially for image, video, embedding, or multimodal models, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.</li><li>
Prior experience with vector search, semantic search, media retrieval, or similarity-matching systems is strongly preferred.</li><li>
Experience mentoring engineers, leading technical discussions, and influencing architectural decisions across backend, infrastructure, and AI/ML workflows.</li></ul><p><b>
Technical Skills</b></p><ul><li>
Strong expertise in Python and/or Node.js with Deep understanding of building scalable RESTful APIs and backend architectures</li><li>
Experience with HuggingFace transformers ecosystem and deep learning frameworks such as PyTorch and TensorFlow.</li><li>
Strong experience with SQL/NoSQL databases, schema design, and data modeling</li><li>
Preferred Exposure to distributed systems, microservices, asynchronous processing, and event-driven patterns with SQS, Pub/Sub, Kafka, or other queueing/pub-sub systems</li><li>
Experience deploying production systems on AWS, GCP, or similar cloud platforms</li><li>
Knowledge of infrastructure patterns (compute, storage, networking, observability)</li></ul><p><b>
AI/ML Integration</b></p><ul><li>
Experience orchestrating embedding generation, scene detection, OCR, speech-to-text, image classification, video analysis, and multimodal model integrations.</li><li>
Experience optimizing inference workflows for latency, throughput, reliability, and cost.</li><li>
Experience working with scalable and optimized inference settings, including tuning sampling parameters, managing output‑length formats, and configuring reasoning‑related behaviors.</li><li>
Familiarity with practical model optimization techniques such as batching, caching, quantization, model distillation, prompt optimization, fallback routing, and use of smaller models where appropriate.</li><li>
Experience working with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services is preferred.</li><li>
Experience working with LLM and Multi-modal evaluation and benchmarking frameworks and domain‑specific benchmarks with the ability to interpret results and optimize model performance accordingly.</li></ul><p><b>
System Design &amp; Architecture</b></p><ul><li>
Preferred understanding of distributed systems, scaling patterns, and performance engineering</li><li>
Ability to design modular, maintainable, and efficient architectures</li><li>
Experience with API versioning, modularization, and designing long-running workflows</li><li>
Understanding of performance bottlenecks and low-latency backend patterns</li></ul><p></p><p><b>
Important information for candidates</b><br>
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:</p><ul><li><b>
Apply only through our official channels.</b> We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li><b>
Verify the recruiter&rsquo;s identity.</b> All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li><b>
Be cautious of unusual communication methods.</b> We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li><b>
Double-check email addresses.</b> All communication from us will come from emails ending in <b>@</b>tether.to<b> or @</b>tether.io</li><li><b>
We will never request payment or financial details.</b> If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul><p><b>
When in doubt, feel free to reach out through our official website.</b></p></div>

Machine Learning Systems Engineer

Spotify

<div><div><div><div><div><div>Data, Research &amp; Insights</div></div></div><div><div>
Data Science</div></div></div><div><div>
Permanent</div></div><div><div>
Dubai</div></div><div><div><div>
<p>
We are looking for a Data Scientist to join the Business Analytics team at Spotify. You will work with the Regional Analytics Lead to evaluate and influence our growth strategy in Middle East &amp; Africa exciting and diverse landscape.</p>
<p>
You will collaborate with a distributed team of world-class analysts, data scientists, business leaders, marketers, and engineers. Learning and improving is part of our daily routine, and you will get a platform to develop your data skills and carve out efficient ways of working.</p>
<p>
The Business Analytics team is part of Spotify&rsquo;s core business strategy organization. You&rsquo;ll play a crucial role in the growth and direction of Spotify as we grow to 760M+ users around the globe.</p>
<p>
At your fingertips, you&rsquo;ll have access to all the data Spotify has to offer, and the opportunity to be creative with how you use it to derive insights and strategies. Above all, your work will impact the way the world experiences audio (and video)!</p>
</div></div></div></div><div><div><p>
What You'll Do
</p><ul><div><ul><li>Develop data driven strategies to drive the growth of Spotify users and subscribers</li>
<li>Identify new user growth levers in the SAMEA region and use experimentation to help drive that growth</li>
<li>Create and communicate impactful recommendations and models that improve our product offering, user messaging, and channel optimization</li>
<li>Build scalable data pipelines and dashboards to facilitate business performance tracking</li>
<li>Work closely with business partners to understand the change they are driving and help them discover new opportunities for growth</li>
<li>Design and implement comprehensive tests, making sure that we track all relevant metrics and that we&rsquo;re learning at every step along the way</li>
<li>Present your findings to senior collaborators, influencing the course of our business</li>
</ul>
</div></ul></div></div><div><div><p>Who You Are</p><ul><div>
<ul>
<li>You have a least 2+ years of professional experience synthesizing insights from data using tools such as Python/R, SQL</li>
<li>Experience with distributed systems and cloud data platforms (BigQuery or GCP) is a plus</li>
<li>Experience with AI tools (LLMs and coding assistants) is a plus</li>
<li>Intellectually curious, creative, and diligent - you enjoy thinking about the business as much as about the data</li>
<li>Have experience collaborating with partners to measure the impact of business/marketing initiatives and presenting those findings in coherent recommendations</li>
<li>Have a background in Economics, Computer Science, Statistics, Engineering or a relevant field</li>
<li>Comfortable working on a globally distributed team (with occasional international travel)</li>
<li>Relevant experience in a consumer tech/product company is a plus</li>
</ul>
</div></ul></div></div><div><div><p>Where You'll Be
</p><ul><ul><li>This role will be based at Spotify&rsquo;s office in Dubai</li>
<li>We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home</li>
</ul></ul></div></div><div><div><p>
Our global benefits</p></div><div></div><div><div>
Extensive learning opportunities, through our dedicated team, GreenHouse.</div></div><div></div><div><div>
Flexible share incentives letting you choose how you share in our success.</div></div><div></div><div><div>
Global parental leave, six months off - for all new parents.</div></div><div></div><div><div>
All The Feels, our employee assistance program and self-care hub.</div></div><div></div><div><div>
Flexible public holidays, swap days off according to your values and beliefs.</div></div></div></div><div></div>

Data Scientist

Ezra

<div><p><b>Predictive Analyst</b></p><br>
<p></p>
<p><b>
Location:</b> Dubai, United Arab Emirates or Nairobi, Kenya</p>
<p><b>
Reports to:</b> Director of Prediction &amp; Data</p><br>
<p></p>
<h3 class="jobSectionHeader"><b>
About the role:</b></h3>
<p>
We are seeking an experienced Data / Decision Scientist<b> </b>to join our team. As a <b>Predictive Analyst</b>, you will be working with and enhancing our prediction pipelines code base, to enable prediction at scale across our many jurisdictions and within EZRA's array of credit products (term and revolving), and to drive new and existing business performance - specifically focused on balancing revenue and bad debt, i.e. net revenue optimisation.</p>
<p>
You will be responsible for designing and developing tools to enable fast model development, conducting experiments, and developing data-driven solutions to solve complex problems.</p>
<p>
The ideal candidate should have strong analytical and problem-solving skills, in addition to high proficiency in <b>Python </b>and <b>SQL</b>, with experience in developing machine learning systems utilizing software engineering principles.</p>
<p>
Previous experience in <b>fintech</b>, specifically <b>credit decisioning</b> systems, <b>airtime credit services </b>or <b>mobile money lending</b> leveraging alternate data is further advantageous.</p><br>
<p></p>
<h3 class="jobSectionHeader"><b>
Key responsibilities:</b></h3>
<ul><li><b>Data Strategy &amp; Preparation:</b> Review and identify key datasets from partners to develop robust ML models. Collect, preprocess, and analyze large, complex datasets to ensure data integrity.</li>
<li><b>Feature Engineering:</b> Define features and perform advanced clustering, feature reduction, and selection techniques.</li>
<li><b>Model Development:</b> Build predictive models to improve partner and product performance, developing specific &quot;Ezra Prediction&quot; modules in Python for automated ML systems.</li>
<li><b>Experimental Design:</b> Design and conduct experiments (A/B testing) to validate models and hypotheses, enhancing overall market understanding.</li>
<li><b>Deployment &amp; Collaboration:</b> Partner with cross-functional teams to implement and deploy machine learning solutions into production environments.</li>
<li><b>Insight Communication:</b> Translate complex findings into actionable insights for both technical and non-technical stakeholders through reports and visualizations.</li>
<li><b>Optimization:</b> Continuously monitor and iterate on model performance, prediction systems, and underlying algorithms.</li></ul><br>
<p></p>
<h3 class="jobSectionHeader"><b>
Essential Qualifications and Experience:</b></h3>
<ul><li><b>Education: </b>Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.</li>
<li><b>Professional Experience:</b> 5+ years of experience in a Data / Decision Science or Machine Learning Engineering role with a proven track record.</li>
<li><b>Technical Proficiency:</b></li>
<li><ul><li>Expert-level Python programming skills.</li>
<li>Advanced SQL skills (Postgres, Redshift, or similar).</li>
<li>Deep understanding of data structures (lists, dictionaries, arrays, data frames).</li>
<li>Data visualization / analysis / statistical inference.</li>
</ul></li><li><b>Core Competencies:</b> Strong analytical and problem-solving skills, with the ability to work effectively both independently and within a team.</li>
<li><b>Communication:</b> Exceptional story-telling and presentation skills, specifically the ability to bridge the gap between technical complexity and business logic.</li>
</ul><h3 class="jobSectionHeader"><b>Beneficial Qualifications and Experience:</b></h3>
<ul><li><b>MLOps &amp; Production:</b> Experience operationalizing ML models into production with measurable impact on product and financial optimization.</li>
<li><b>DevOps Tools:</b> Proficiency with Source Control Management (Git/Bitbucket) and CI/CD pipelines (e.g., Jenkins).</li>
<li><b>Architecture:</b> Understanding of Feature Store architecture and implementation.</li>
<li><b>Environment:</b> Experience working in Linux OS variants (Debian) and comfort utilizing the command line.</li>
<li><b>Agility:</b> Ability to balance &quot;start-up&quot; stage project work with the development of long-term scalable ML modules.</li>
<li><b>Language Skills:</b> Proficiency in <b>French</b> is beneficial to support operations across various jurisdictions.</li>
</ul><h3 class="jobSectionHeader"><b>The Ideal Candidate:</b></h3>
<ul><li><b>Innovation-Driven:</b> Passionate about deploying customer-centric products that exceed quality and delivery expectations.</li>
<li><b>Growth Mindset:</b> Proud of their work but driven by continuous improvement; able to self-critique and accept constructive feedback.</li>
<li><b>Detail-Oriented:</b> High attention to detail with a commitment to process, procedure, and documentation as pillars of excellence.</li>
<li><b>Adaptable:</b> Comfortable stepping outside of their comfort zone to learn new tasks and technologies.</li>
</ul><h3 class="jobSectionHeader"><b>Company overview:</b></h3>
<p>
Ezra provides B2B digital lending solutions for emerging markets in partnership with mobile and digital wallet operators and financial service providers. Ezra supports 24 operations in 23 countries, across Africa, the Middle East and Asia. Our key office locations are in Nairobi, Kenya and Dubai, UAE.</p>
<p>
Our flagship products are Airtime Credit Services (ACS), Nano and BNPL.</p>
<ul>
<li>ACS is an airtime or data advance offered to prepaid mobile subscribers at the point of low credit.</li>
<li>Nano is a micro cash advance offered to mobile wallet users on demand.</li>
<li>BNPL facilitates payment installments for products and services</li></ul><br>
<p></p>
<p>
As a FinTech company, our business is entirely technology and data driven, from determining subscriber eligibility, generating relevant offers, managing risk, loan issuance, recovery, optimizing performance and reporting, reconciliation and billing.</p><br>
<p></p>
<p>
Each day we process approximately 21M loan requests and 1.4 TB of data across our markets. This process needs to be robust, reliable and secure.</p><br>
<p></p>
<p>
But it doesn't end there. We're exploring new ways of using our platform and transactional data to improve our products and develop new product opportunities.</p></div>

Predictive Analyst

Al Fattan Properties

<div><div><b>Job Description:</b></div><ul><li>
Completes construction projects by preparing engineering design and documents and confirming specifications.</li><li>
Designs construction projects by studying project concept, architectural drawings, and models.</li><li>
Prepares engineering design by collecting and studying reports, maps, drawings, blueprints, aerial photographs, and tests on soil composition, terrain, hydrological characteristics, and related topographical and geologic data.</li><li>
Determines project costs by calculating labor, material, and related costs.</li><li>
Creates feasibility study by analyzing engineering design, conducting environmental impact studies, and assembling data.</li><li>
Produces engineering documents by developing construction specifications, plans, and schedules.</li><li>
Confirms adherence to construction specifications and safety standards by monitoring project progress, inspecting construction site, and verifying calculations and placements.</li><li>
Fulfills project requirements by training and guiding operators.</li><li>
Maintains operations by enforcing project and operational policies and procedures.</li><li>
Provides engineering information by answering questions and requests.</li><li>
Complies with federal, state, and local legal requirements by studying existing and new legislation; anticipating future legislation; enforcing adherence to requirements; and advising management on needed actions.</li><li>
Maintains project database by writing computer programs, entering data, and completing backups.</li><li>
Contributes to team effort by accomplishing related results as needed.</li></ul><div><br>
<b>
Civil Engineer Qualifications/Skills:</b></div><ul><li>
CAD and AutoCAD proficiency</li><li>
Design skills</li><li>
Site development</li><li>
Database design</li><li>
Planning</li><li>
Conceptual skills</li><li>
Legal compliance</li><li>
Drafting, LISP</li><li>
Problem-solving</li></ul><div><br>
<b>
Education, Experience, and Licensing Requirements:</b></div><ul><li>
Bachelor&rsquo;s degree in civil/structural engineering, architectural engineering, or architecture</li><li>
PE is required for an engineer or RA is required for an architect</li><li>
4 to 5 years of engineering or architectural experience.</li></ul></div>

Junior Architect

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