estimation engineer

planning engineer

project engineer

business analyst

data scientist

data engineer

Confidential

<div>
 
 
 Job Summary
 
 
 
 We are seeking a
 
 Senior / Lead Data Engineer
 
 to design, build, and scale
 
 AI-powered, cloud-native data platforms
 
 that support enterprise analytics, machine learning, and business-critical decision-making.
 
 
 The ideal candidate will bring deep expertise in
 
 data engineering, cloud data warehouses, cost optimization, and AI-assisted development
 
 , with a proven track record of delivering
 
 high-impact, revenue-generating data platforms
 
 and
 
 intelligent automation solutions
 
 at scale.
 
 
 
 Key Responsibilities
 
 
 
 
 Data Platform &amp; Pipeline Engineering
 
 
 <ul>
 <li>
 Design, develop, and maintain
 
 scalable ETL/ELT pipelines
 
 using Python, SQL, dbt, and modern orchestration tools.
 </li>
 <li>
 Build and optimize
 
 cloud-based data warehouses
 
 (BigQuery or equivalent) supporting high-volume analytical workloads.
 </li>
 <li>
 Implement
 
 robust data modeling
 
 (dimensional and analytical models) to enable self-service analytics and AI use cases.
 </li>
 <li>
 Ensure
 
 data quality, integrity, and freshness
 
 through automated validation frameworks and monitoring.
 </li>
 </ul>
 
 
 AI-Driven Automation &amp; Innovation
 
 
 <ul>
 <li>
 Design and deploy
 
 AI-powered internal tools and agents
 
 to automate data engineering workflows, incident diagnosis, and root cause analysis.
 </li>
 <li>
 Integrate AI agents with collaboration tools (e.g., Slack) to improve operational efficiency and reduce incident resolution time.
 </li>
 <li>
 Apply AI-assisted development techniques to accelerate delivery, improve code quality, and reduce manual effort across teams.
 </li>
 </ul>
 
 
 Performance &amp; Cost Optimization
 
 
 <ul>
 <li>
 Lead
 
 cloud cost optimization initiatives
 
 , including query optimization, architectural redesign, and usage monitoring.
 </li>
 <li>
 Drive measurable reductions in data platform operational costs while maintaining performance and reliability.
 </li>
 </ul>
 
 
 Cloud &amp; DevOps
 
 
 <ul>
 <li>
 Build and deploy data services using
 
 containerized and CI/CD-driven workflows
 
 .
 </li>
 <li>
 Collaborate with DevOps and platform teams to ensure scalable, secure, and reliable cloud infrastructure.
 </li>
 <li>
 Support multi-cloud or hybrid environments as required (GCP, Azure).
 </li>
 </ul>
 
 
 Leadership &amp; Collaboration
 
 
 <ul>
 <li>
 Provide
 
 technical leadership and mentorship
 
 to data engineers.
 </li>
 <li>
 Establish
 
 SOPs, best practices, and engineering standards
 
 across the data function.
 </li>
 <li>
 Partner closely with product, analytics, and business stakeholders to translate requirements into scalable data solutions.
 </li>
 </ul>
 
 
 Required Skills &amp; Qualifications
 
 
 
 
 Technical Skills
 
 
 <ul>
 <li>
 
 Programming:
 
 Python (expert), SQL (expert), Shell scripting (advanced).
 </li>
 <li>
 
 Data Engineering:
 
 dbt, ETL/ELT pipelines, data warehousing, data modeling, data quality frameworks.
 </li>
 <li>
 
 Cloud Platforms:
 
 Google Cloud Platform (BigQuery, Cloud Run) &ndash; strong experience; Azure familiarity is a plus.
 </li>
 <li>
 
 Orchestration &amp; Automation:
 
 Airflow or equivalent.
 </li>
 <li>
 
 DevOps &amp; Tooling:
 
 Git, Docker, CI/CD pipelines.
 </li>
 <li>
 
 AI &amp; ML Exposure:
 
 AI agent frameworks, ML pipelines, model lifecycle management, observability tools.
 </li>
 </ul>
 
 
 Data Management
 
 
 <ul>
 <li>
 Cost optimization and performance tuning.
 </li>
 <li>
 Data governance, cataloging, and best-practice documentation.
 </li>
 </ul>
 
 
 Education
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science or related field.
 </li>
 <li>
 Master&rsquo;s or Postgraduate qualification in Data Science is preferred.
 </li>
 </ul>
 
 
 Nice to Have
 
 
 <ul>
 <li>
 Experience delivering
 
 AI/ML pipelines
 
 in production environments.
 </li>
 <li>
 Exposure to
 
 government, public sector, or regulated enterprise data platforms
 
 .
 </li>
 <li>
 Experience building
 
 observability and monitoring tools
 
 for data platforms.
 </li>
 <li>
 Prior work on
 
 Arabic-language or regional datasets
 
 .
 </li>
 </ul>
 
 
</div>

Data Engineer

Khazna Data Centers

<div>
 
 
 Khazna was founded in 2012 and has grown rapidly into becoming the leading and trusted wholesale Data Center provider in the Middle East and North Africa region. Through our Data Centers, we provide industry benchmark levels of power supply and cooling services to better serve the growing need for data center operations in the UAE and wider region.
 
 
 
 
 
 
 We are seeking a
 
 Data Engineer
 
 to join our
 
 Command &amp; Control Center &ndash; Data Analytics &amp; Reporting
 
 team, reporting to the
 
 Manager, Data &amp; BI
 
 . This centralized role is responsible for designing, developing, and maintaining scalable data pipelines that support analytics, reporting, and AI/ML initiatives for data center operations. The Data Engineer will ensure data integrity, optimize data architecture, and manage ETL (Extract, Transform, Load) processes across cloud and on-premises platforms to enable effective, data-driven decision-making.
 
 
 
 
 
 
 Key Accountabilities:
 
 
 
 
 
 <ul>
 <li>
 Support the development of scalable data warehouses, lakes and resilient data pipelines to support high-velocity data processing in a wholesale data center environment
 </li>
 <li>
 Design and implement Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes to clean, normalize and transform data from diverse sources, including Internet of Things (IoT) sensors, Building Management System (BMS) within data center operations
 </li>
 <li>
 Automate data ingestion, transformation and storage workflows for real-time analytics, ensuring low-latency insights for operational decision-making across data center environments
 </li>
 <li>
 Set up streaming data services to enable continuous migration of critical data center infrastructure metrics into analytics platforms for real-time monitoring
 </li>
 <li>
 Work with Integration teams, Data Warehouse engineers and Analytics teams to build highly optimized, resilient and scalable data center data processing architectures
 </li>
 <li>
 Define data sourcing strategies, tagging mechanisms and aggregation methods to ensure seamless availability of structured and unstructured data for data center analytics
 </li>
 <li>
 Collaborate with Data Scientists and Business Intelligence (BI) teams to enable AI/ML model development, predictive analytics and operational intelligence for data center operations
 </li>
 <li>
 Develop calculation methodologies for statistical computation of KPIs related to Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), uptime and asset utilization in data centers
 </li>
 <li>
 Identify critical data points and sources that drive KPI computations and aggregate site-level metrics for centralized data center performance reporting
 </li>
 <li>
 Build reporting source files for dashboards, enabling executive leadership to monitor data center performance trends across regional and site-level operations
 </li>
 <li>
 Generate historical trend analyses, benchmarking individual data center site performance against portfolio-wide averages to drive efficiency improvements
 </li>
 <li>
 Conduct Exploratory Data Analysis (EDA) to identify patterns, anomalies and correlations that impact energy efficiency, workload distribution and infrastructure health in data centers
 </li>
 <li>
 Gather required historical and real-time data from internal platforms and external sources, ensuring comprehensive datasets for advanced analytics in data center environments
 </li>
 <li>
 Develop simulations and scenario models to analyse potential business impacts, optimize data center capacity planning and mitigate operational risks
 </li>
 <li>
 Update models and forecasting frameworks based on market trends, data center infrastructure expansion plans and internal priority shifts
 </li>
 <li>
 Research and implement cutting-edge data engineering techniques, contributing to industry-leading best practices in large-scale data center data infrastructure management
 </li>
 <li>
 Deliver data archiving, backup and disaster recovery strategies, ensuring high availability and business continuity for critical data center data assets
 </li>
 <li>
 Ensure seamless integration of data platforms with enterprise applications, enabling end-to-end visibility and automated decision-making across the data center ecosystem
 </li>
 </ul>
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or master&rsquo;s degree in computer science (or) related to Data Engineering
 </li>
 <li>
 Certifications in cloud data platforms preferred
 </li>
 <li>
 4+ years of experience in data engineering, ETL development or database management
 </li>
 <li>
 Strong proficiency in SQL, Python or Scala
 </li>
 <li>
 Experience with cloud data platforms (AWS, Azure, GCP)
 </li>
 <li>
 Hands-on experience with data pipeline tools like Apache Airflow, Kafka or Spark
 </li>
 <li>
 Understanding of data modeling, warehousing and governance principles
 </li>
 </ul>
 
 
 
 
 
 Additional skills:
 
 
 
 
 
 <ul>
 <li>
 Ability to troubleshoot complex data challenges, optimize pipeline performance and drive continuous improvements in large-scale infrastructure
 </li>
 <li>
 Strong ability to work across Data Science, Engineering, IT and Business Intelligence teams to align data solutions with business needs
 </li>
 <li>
 Expertise in translating technical data models and engineering concepts into clear insights for non-technical stakeholders
 </li>
 </ul>
 
 
 
 
 
 Training/Certifications Preferred:
 
 
 
 
 
 <ul>
 <li>
 AWS Certified Data Analytics &ndash; Specialty
 </li>
 <li>
 Google Professional Data Engineer
 </li>
 <li>
 Microsoft Certified: Azure Data Engineer Associate
 </li>
 <li>
 Apache Spark Developer Certification
 </li>
 </ul>
 
 
</div>

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.
 
 
 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.
 
 
 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.
 
 
 
 Responsibilities
 
 
 
 <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
 
 
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <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)
 
 
 
 
 </li>
 </ul>
 Join us as we embark on this journey to redefine the future of biology and medicine.
 
 
 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.
 
 
 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

Dizzaract FZ LLC

About DizzaractDizzaract is a UAE-based game development studio founded in 2022, headquartered at Yas Creative Hub, Abu Dhabi. We develop cutting-edge AI-powered games and systems, including our innovation R&amp;D laboratory FAR labs, the upcoming hero shooter Farcana, and the AI gaming identity platform GAMED. Our research and development team boasts over 100 peer-reviewed papers and more than 20 patents in AI-driven gameplay, digital ownership, and competitive design. With a diverse team of more than 80 professionals from over 20 countries, we are committed to innovation, excellence, and building a culture that drives performance and results.The Mission: An inference network routing millions of requests globally generates a massive, complex data exhaust. You will build the data plane that fuels our routing intelligence, telemetry, and distributed memory systems. To beat OpenRouter, our network needs to route requests intelligently based on real-time hardware metrics and cost analysis without adding latency.What You Will Do:<ul><li>High-Throughput Telemetry: Design pipelines to ingest, process, and analyze millions of telemetry events per second (GPU utilization, TTFT, inter-token latency) from distributed nodes.</li><li>Distributed KV-Cache Architecture: Architect the data layer for distributed KV-cache storage and retrieval, allowing the network to context-switch efficiently across different compute nodes.</li><li>Intelligent Routing State: Build the real-time data stores that power our routing layer, ensuring the network always knows the exact state, cost, and availability of every node globally.</li><li>Ledger &amp; Analytics: Develop the backend pipelines for billing, rate-limiting, and auditing, ensuring airtight data consistency for high-frequency micro-transactions.</li><li>Data Packaging: Ensure all data infrastructure deployments are containerized, immutable, and require zero manual configuration upon deployment.</li></ul>What We Are Looking For:<ul><li>Expertise in high-throughput messaging and streaming systems (e.g., Redpanda, Kafka) and real-time OLAP databases (e.g., ClickHouse).</li><li>Strong proficiency in backend languages (Rust, Go, or Python) with a focus on high concurrency and low latency.</li><li>Experience with vector databases and managing massive, distributed state.</li><li>A strong grasp of distributed consensus algorithms and data replication across decentralized environments.</li></ul>Work Location: In person

AI Inference Data Engineer

Etihad

<div>
 Synopsis
 
 
 
 
 As a Data Scientist your primary responsibility is to utilize data to improve various aspects of the airline's operations. Apply advanced statistical and machine learning techniques to develop AI-driven solutions aimed at enhancing efficiency and customer experiences. Analyze data, predicting trends, and optimizing processes across different operational areas, contributing to incremental improvements in the airline's performance and competitiveness.
 
 
 Accountabilities
 
 
 
 
 
 Data Analysis and Modeling:
 
 
 
 <ul>
 <li>
 Conduct in-depth analysis of large and complex datasets to extract meaningful insights and identify actionable opportunities for improvement.
 
 
 </li>
 </ul>
 
 Algorithm Development:
 
 
 
 <ul>
 <li>
 Design, develop, and deploy cutting-edge predictive models and algorithms that address key challenges and opportunities within the aviation industry.
 
 
 </li>
 </ul>
 
 Optimization and Automation:
 
 
 
 <ul>
 <li>
 Continuously refine and optimize machine learning models to improve accuracy, efficiency, and scalability, while also exploring opportunities for automation to streamline processes and reduce manual effort.
 
 
 </li>
 </ul>
 
 Collaboration and Innovation:
 
 
 
 <ul>
 <li>
 Collaborate closely with cross-functional teams including software engineers, aviation experts, and business stakeholders to co-create innovative solutions that address real-world challenges and deliver tangible business value.
 
 
 </li>
 </ul>
 
 Research and Development:
 
 
 
 <ul>
 <li>
 Stay abreast of the latest advancements in data science, AI, and aviation technology, and proactively explore emerging trends and methodologies to drive continuous innovation and improvement.
 
 
 </li>
 </ul>
 
 Communication and Stakeholder Engagement:
 
 
 
 <ul>
 <li>
 Effectively communicate findings, insights, and recommendations to technical and non-technical stakeholders through clear, compelling presentations and reports, and actively engage with stakeholders to gather feedback and ensure alignment with business objectives.
 
 
 </li>
 </ul>
 Education &amp; Experience
 
 
 
 
 <ul>
 <li>
 Bachelor's degree or higher in Computer Science, Statistics, Mathematics, Data Science, Aviation Engineering, or a related field.
 </li>
 <li>
 5-7 years&rsquo; experience working as a Data Scientist or similar role, preferably in aviation or a related field.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, or Java, as well as experience with data manipulation and analysis libraries (e.g., pandas, numpy, scikit-learn).
 </li>
 <li>
 Strong understanding of machine learning techniques and algorithms such as regression, classification, clustering, neural networks, etc., with experience applying to real-world problems.
 </li>
 <li>
 Familiarity with data visualization tools such as Tableau, Power BI, or matplotlib.Knowledge of aviation operations and industry-specific challenges and opportunities is desirable.
 </li>
 <li>
 Excellent problem-solving skills, attention to detail, and the ability to work effectively both independently and as part of a team.
 </li>
 <li>
 Strong communication and interpersonal skills, with the ability to effectively collaborate with colleagues across various disciplines and levels of the organization.
 
 
 </li>
 </ul>
 
 About Etihad Airways
 
 
 
 Etihad Airways, the national airline of the UAE, was formed in 2003 and quickly went on to become one of the world&rsquo;s leading airlines. From its home in Abu Dhabi, Etihad flies to passenger and cargo destinations in the Middle East, Africa, Europe, Asia, Australia and North America. Together with Etihad&rsquo;s codeshare partners, Etihad&rsquo;s network offers access to hundreds of international destinations. In recent years, Etihad has received numerous awards for its superior service and products, cargo offering, loyalty programme and more. All this ties into Etihad&rsquo;s ambitious Journey 2030 strategy. The airline plans to double its fleet size and triple the number of customers over the next six years as it sets out to be the airline everyone wants to fly!
 
 
 To learn more, visit etihad.com
 
 
 
 Recruitment Fraud Alert
 
 
 
 Beware of fraudulent job offers from individuals or organizations claiming to represent the Etihad group. We will never ask for personal information, bank details, or payment during the recruitment process. Interviews are conducted face-to-face or via video/telephone before any formal offer. If you are asked for money, please treat it as fraudulent.
</div>

Data Scientist

ADGM

Maseera&rsquo;s AI and Big Data Center of Excellence covers the range of Data and AI skills, from Strategy, Governance, Data Science, Data Architecture, AI Engineering and Visual Insights. When combined with Maseera&rsquo;s broader Strategy and professional practice, we are bringing together the unique ability to drive end-to-end business change through the application of Data and AI. You'll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways.If you&rsquo;re looking for a challenging career while working in a vibrant environment with access to training and a global network of experts, this could be the role for you. As part of our global team, you'll be based in Abu Dhabi, and you&rsquo;ll be working with cutting-edge technologies, and you will have the opportunity to develop a wide range of new skills on the job.In our team you will:<ul><li>Be at the forefront of the Fintech industry, and you&rsquo;ll create, own and make it a reality for our subsidiaries looking to better serve their customers.</li><li>Become an integral part of our Data and AI team with the credibility, expertise and dependable insights.</li><li>Develop your skills with our world class training programmes.</li><li>Drive and implement real world solutions into production that drive business value across our company.</li><li>Work alongside global teams to collaborate and deliver the best solutions for our customers.</li><li>Drive your career progression via our structured career development programs.</li></ul>In this role you will:<ul><li>Solve challenging business problems using advanced machine learning methods such as Deep Learning and quantitative analytics.</li><li>Understand business requirements and support the development of business cases.</li><li>Run discovery analytics to identify new and innovative opportunities.</li><li>Partner with developers and engineers to deploy machine learning algorithms to deliver business value.</li><li>Define approaches to embed and scale machine learning models.</li><li>Build reusable assets and solutions and develop best practices for current and future business problems.</li><li>Communicate and provide guidance to senior leadership and teams.</li><li>Contribute data science expertise to new enterprise activities.</li><li>Shape DS Strategy and the delivery of DS solutions.</li><li>Operate across Headquarter and multiple subsidiaries.</li><li>Develop others by bringing your unique knowledge and skill sets to the wider practice.</li></ul>We are looking for:<ul><li>B.Sc./Master/PhD in computer science, data science, AI or relevant field</li><li>8-10 years of work experience in data science, machine learning, and business analytics</li><li>Practical experience in coding languages e.g. Python, R, Scala, etc.; (Python preferred)</li><li>Proficiency in database technologies e.g. SQL, ETL, No-SQL, DW, and Big Data technologies e.g. pySpark, Hive, etc.</li><li>Experienced working with structured and also unstructured data e.g. Text, PDFs, jpgs, call recordings, video, etc.</li><li>Knowledge of machine learning modelling techniques and how to fine-tune those models e.g. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc.</li><li>Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, hugging face, etc.</li><li>Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge.</li><li>Experience of using Cloud technologies e.g. AWS, GCP or Azure.</li><li>Specialised visualisation techniques e.g. D3.js, ggplot etc.</li><li>Strong verbal/written communication &amp; data presentation skills</li><li>Awareness of Large Language Models (LLMs) and a strong enthusiasm for continuous learning and staying updated with the latest advancements in the field</li></ul>Set yourself apart:<ul><li>Willingness and ability to learn quickly and apply creative thinking to finding great solutions and drive their implementation</li><li>Ability to successfully build relationships with customers and stakeholders</li><li>Mastery of problem solving and solutioning</li><li>Proven history and background in Fintech Industry</li></ul>Job Type: Full-timePay: AED35,000.00 per monthExperience:<ul><li>Financial Institues: 3 years (Required)</li></ul>Location:<ul><li>Abu Dhabi (Required)</li></ul>Work Location: In person

Senior Data Scientist

ALTÉRRA

<div>
 
 
 Firm Overview
 
 
 
 
 
 
 ALT&Eacute;RRA is a $30 billion catalytic climate investment fund designed to mobilize capital at scale and accelerate the transition to a climate-resilient economy. Our mission is to activate and expand the global climate finance ecosystem by stimulating innovation, unlocking private capital, and reducing investment barriers in emerging markets and developing economies (EMDEs).
 
 
 
 
 
 With a strong emphasis on actionable, high-impact investments, ALT&Eacute;RRA deploys capital through a combination of fund investments, co-investments, and direct investments, supporting best-in-class managers and projects that align with our climate and financial objectives. Alterra Management Limited, based in ADGM and regulated by the ADGM Financial Services Regulatory Authority, serves as the investment manager for the fund.
 
 
 
 
 
 
 Role Overview
 
 
 
 
 
 
 The successful candidate will support the implementation and ongoing development of ALTERRA&rsquo;s Impact Framework, contributing to the assessment of climate impact and additionality for both potential and existing investments. This role will work closely with the Impact Lead and investment teams, providing technical analysis, advanced data analytics, and data-driven insights to inform decision-making and support ALTERRA&rsquo;s climate impact objectives as well as its interest to enhance investments in the Global South.
 
 
 
 
 
 
 Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Contribute to the assessment of climate impact, including emissions of existing and potential investments, supporting due diligence and investment processes in alignment with ALTERRA&rsquo;s Impact Framework.
 </li>
 <li>
 Prepare technical analyses and initial screenings of investment opportunities from an impact perspective, leveraging advanced data analytics and quantitative methods.
 </li>
 <li>
 Collect, clean, and analyse large datasets related to climate/impact performance, using statistical and machine learning techniques where appropriate.
 </li>
 <li>
 Support the preparation of materials and recommendations for the Investment Committee regarding climate considerations in potential deals
 </li>
 <li>
 Assist in the development and updating of guidance materials for investment teams to ensure consistent, high-quality integration of climate and additionality impact.
 </li>
 <li>
 Contribute to the preparation of materials from external partners to clarify ALTERRA&rsquo;s expectations, including reporting needs and data submission standards.
 </li>
 <li>
 Support the assessment of climate risk and potential financial impacts on ALTERRA&rsquo;s investments, providing robust data analysis to inform due diligence and valuation.
 </li>
 <li>
 Stay informed on the latest climate science, related policies, data analytics tools, and relevant frameworks, contributing insights to ensure the Impact Framework remains current.
 </li>
 <li>
 Collaborate with internal and external stakeholders, sharing technical expertise and supporting cross-functional teams.
 </li>
 <li>
 Support climate impact measurement and reporting activities as required, ensuring data integrity and consistency.
 </li>
 <li>
 Other research and content development as needed, playing a cross-functional role within the Impact team to support ALTERRA&rsquo;s continued growth, including conducting research deep dives and analysis related to a particular impact sector or research theme, helping to support on the development of a critical organizational team function
 </li>
 </ul>
 
 
 
 
 
 Experience and Qualifications
 
 
 
 
 
 <ul>
 <li>
 At least 5 years of relevant experience in climate impact research, sustainable finance, or a related field, with a strong focus on data analytics and integration of climate considerations into investment processes.
 </li>
 <li>
 Assessment experience with emerging markets a plus, as well as working for an established financial institution.
 </li>
 <li>
 Technical proficiency in climate science and policies, environmental policies, and sustainability frameworks (e.g., IPCC, IEA, GIIN, IMP).
 </li>
 <li>
 Demonstrated experience with data analytics tools and programming languages a plus (e.g., DataIKU, KNIME, Python, R, SQL), and data visualization platforms (e.g., Power BI, Tableau).
 </li>
 <li>
 Strong analytical and quantitative skills, with the ability to interpret and communicate complex data to both technical and non-technical audiences, and navigate challenges with creative problem-solving ability
 </li>
 <li>
 Experience preparing technical reports, dashboards, and presentations.
 </li>
 <li>
 Collaborative team player, able to work effectively in a fast-paced, cross-functional environment with tight timelines.
 </li>
 <li>
 Bachelor&rsquo;s degree in economics, econometrics, environmental science, data science, sustainable business, finance, or a related field; advanced degree is a plus.
 </li>
 </ul>
 
 
</div>

Explore 684+ Data engineer in Abu Dhabi this April. Find roles across top companies and apply now to boost your career.

684 data engineer jobs In Abu Dhabi

Data Engineer

Data Engineer

Bioinformatics Data Engineer

AI Inference Data Engineer

Data Scientist

Senior Data Scientist

Data Scientist