Qureos Mentor

Emirates Global Aluminium (EGA)

<div>
 
 A Lead Data Engineer works closely with a multidisciplinary Agile team to build high quality data pipelines driving analytic solutions. These solutions will generate insights allowing to advance data-driven decision-making capabilities. This role requires deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. The ideal candidate is a skilled data / software engineer with experience creating data products supporting analytic solutions. They work as part of a technical, cross functional analytics team.
 
 
 
 
 
 
 KEY ACCOUNTABILITIES:
 
 
 
 &squf; Design, develop, optimize, and maintain data architecture and pipelines that adhere to Extract, Transform, and Load (ETL) principles and business goals
 
 
 &squf; Solve complex data problems to deliver insights that helps our business to achieve their goals
 
 
 &squf; Create data products for analytics and data scientist team members to improve their productivity &squf; Advise, consult, mentor and coach other data and analytic professionals on data standards and practices
 
 
 &squf; Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
 
 
 &squf; Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering in order to improve our productivity as a team
 
 
 &squf; Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
 
 
 &squf; Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives
 
 
 &squf; Develop and deliver some data science courses part of advance analytics and digital academy
 
 
 &squf; Performs other duties as assigned.
 
 
 
 
 
 
 QUALIFICATIONS &amp; SKILLS:
 
 
 
 Minimum Qualifications:
 
 
 &squf; Bachelor&rsquo;s degree or MS required; Computer Science, MIS, or Engineering preferred
 
 
 &squf; 5 years of experience working in data engineering or architecture role, 7+ preferred
 
 
 &squf; Expertise in SQL and data analysis and experience with programming language (Python, R or Scala preferred)
 
 
 
 
 
 
 &squf; Minimum Experience:
 
 
 
 &squf; Experience developing and maintaining data warehouses in big data solutions
 
 
 &squf; Should have domain knowledge of metal and mining or energy or heavy industry or oil and gas experience or a combination of either industries.
 
 
 &squf; Good Knowledge of programming languages and developing data analytics models (R, Python, Spark, Java, Scala, etc.)
 
 
 &squf; Experience with dashboard development and BI tools such as Tableau, Power BI, Looker, Shiny, Qlik, etc.
 
 
 &squf;Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (preferred)
 
 
 &squf; Experience in data architecture including the ability to define data retention policies, monitor performance and advise any necessary infrastructure changes
 
 
 &squf; Good knowledge of data and analytics, e.g. dimensional modeling, ETL, reporting tools, data governance and warehousing, structured and unstructured data
 
 
 &squf; Practical knowledge in traditional ETL tools (Informatica, Alteryx, SAP data services etc.) as well as big database systems like the Hadoop ecosystem and cloud technologies (Azure, Spark, etc.)
 
 
 &squf; Database development experience using Hadoop or BigQuery and experience with a variety of relational, NoSQL, and cloud database technologies &squf; Big Data Development experience using Hive, Impala, Spark and familiarity with Kafka (Preferred), familiarity with the different operating system (Preferred)
 
 
 &squf; Exposure to Machine Learning, data science, computer vision, AI, statistics, and/or applied mathematics
 
 
 &squf; Good working knowledge of industry 4.0 application, big data, autonomous robots, system integration, cloud computing, additive manufacturing, augmented reality etc.
 
 
 &squf; Experience in automation &amp; control system and training in similar fields is valued.
 
 
 
 
 
 
 AUTHORITY/ DECISION MAKING:
 
 
 
 &squf; Thinking within broadly defined policies, standards and objectives. The determination of &ldquo;what needs to be done&rdquo; in applying polices is largely left up to the incumbent who must establish the plan, determine the priorities and prescribe the processes needed to achieve the objectives
 
 
 &squf; Subject to general direction and broadly defined functional policy objectives. Actions which will impact other functional or operating areas usually require approval before they may be implemented.
 
 
 
 
 
 
 Agile/Digital skills:
 
 
 
 &squf; Experience working on collaborative Agile product team
 
 
 Individual skills:
 
 
 &squf; Self-motivated with strong problem-solving and learning skills
 
 
 &squf; Flexibility to changes in work direction as the project develops
 
 
 &squf; Excellent communication, listening, and influencing skills
 
 
 
 
 
 Mindset &amp; Behaviors:
 
 
 &squf; Flexibility in quickly adjusting positions based on stakeholders&rsquo; input
 
 
 &squf; Ability to work at an abstract level and gain consensus
 
</div>


Job Id: yWX61fJJtHs6h4AEdvM2Q9YX4M5XnIrIApfKGdJXXRQsPL9eWtxIJ6b0/16calpYmExodLT0+wOFZFup0o2WMSv0M3IDrmwMyQ==

Lead Data Engineer

<div>
 
 JOB PURPOSE:
 
 
 The Head of Data Architecture (DA) holds the reins of data architecture decisions within the team. The Head of Data Architecture (DA) is the strategist driving the overarching data architecture strategy for the digital transformation. Working in close coordination with the business, digital, and IT teams, the Head of Data Architecture (DA) architects the data infrastructure necessary for enabling the digital and advanced AI use cases.
 
 
 The Head of Data Architecture (DA) also nurtures the team&rsquo;s data architecture practices and mentors data engineers on specific use-cases. This role oversees the comprehensive pipeline of data flow and provides guidance to the team in managing workflows seamlessly. Through an understanding of the interdependencies of data systems, the Head of Data Architecture DA ensures the coherent organization of data across multiple platforms and its availability for key business initiatives.
 
 
 
 
 KEY ACCOUNTABILITIES:
 
 <ul>
 <li>
 Data Architecture Design: Lead data architecture design to support real-time event streaming, data products, and different machine learning models solving optimisation, computer vision and LLM&rsquo;s problems. This involves creating blueprints for data management systems to integrate, centralize, protect, and maintain the data sources.
 </li>
 <li>
 System Development: Lead the design and support the implemention of large-scale data processing systems capable of handling the volume, velocity, and variety of data that needs to be analyzed and processed.
 </li>
 <li>
 Data Strategy: Contribute and support of EGA&rsquo;s data strategy, including the use of new technologies and practices, to improve the quality, reliability, and efficiency of data extraction and its use in machine learning and data product applications.
 </li>
 <li>
 Data Modelling &amp; Management: Spearhead the creation and maintenance of conceptual, logical, and physical data models, supporting both operational and AI use cases. Oversee data integrity and quality assurance processes across upstream, midstream and downstream.
 </li>
 <li>
 Machine Learning Framework: Lead the design of the ML OPs framework and define Design workflows and processes that accelerate the development and deployment of machine learning models, ensuring that ML models are production-ready and scalable.
 </li>
 <li>
 Data Governance: Lead and contribute to define policies and procedures for data governance in collaboration with the data protection officer and other stakeholders, ensuring compliance with data privacy and protection laws. Lead efforts of data governance platform integration.
 </li>
 <li>
 Collaboration: Collaborate with IT teams, data engineers, and senior stakeholders to ensure that the data architecture supports and helps achieve strategic objectives. Lead in proposing, buy in and drive the end solution.
 </li>
 <li>
 Communicate effectively complex data concepts, solutions, proposals in simple language to non-technical team members and senior leaders (Senior Director,C level, Executive Committee).
 </li>
 <li>
 Mentorship and Leadership: Act as a mentor to data engineers (4-8), providing guidance and support in their professional development. Promote a culture of performance, collaboration, and continuous learning within the data team.
 </li>
 <li>
 Innovation and Continuous Improvement: Stay up-to-date with industry trends and new technologies. Continuously explore innovative solutions and enhancements to the existing data architecture to improve its scalability, reliability, and efficiency. Championing and driving initiatives like event sourcing, data contracts &amp; schema registries, data lineage and automation downstream.
 </li>
 <li>
 Problem Solving: Drive solutions, anticipate and contribute to resolve technical issues before they become roadblocks, maintaining the continuity of data flow and ensuring the highest levels of data quality and integrity, I.e. alerting &amp; monitoring strategy, change request frame work and automation, scaling up and data partitioning strategy
 </li>
 <li>
 Project Management: Coordinate and indirectly manage data-related projects (15-20 use cases every 3 month waves), ensuring they are completed on time and within budget, meeting or exceeding stakeholder expectations.
 </li>
 </ul>
 
 
 
 AUTHORITY/ DECISION MAKING:
 
 <ul>
 <li>
 Design authority on data architecture, governance and technology selection to support scale up ambitions of 50-60 usecases a year.
 </li>
 <li>
 Validate data security protocols and resource allocation decisions based on usecase requirements.
 </li>
 <li>
 Validation of technical design and solutions to support 10 digital capabilities based on industry4.0 principles
 </li>
 </ul>
 
 
 
 
 QUALIFICATIONS &amp; SKILLS:
 
 
 Domain Expertise
 
 <ul>
 <li>
 Bachelor&rsquo;s degree required, MS or PhD preferred
 </li>
 <li>
 Bachelor&rsquo;s in Data Science, Computer Science, Engineering, Statistics and 10+ years of relevant experience.
 </li>
 <li>
 Minimum 10+ years of data architecture experience utilising strong leadership skills, including mentoring, communication, decision-making, and project management.
 </li>
 <li>
 Expert knowledge of the Big Data technology landscape beyond the buzzwords; Hands on experience with big data platforms and tools such as Python, Spark, NoSQL, Key Value stores
 </li>
 <li>
 Expert with batch and real-time processing frameworks (Apache Kafka, Apache Spark etc.)
 </li>
 <li>
 Expert design knowledge and hands on experienceof designing data pipelines and workflow management tools like Airflow, relevant NiFi, or Luigi.
 </li>
 <li>
 Expertise of machine learning platforms and tools like TensorFlow, PyTorch, or scikit-learn.
 </li>
 <li>
 Data frameworks suitable for LLM&rsquo;s
 </li>
 <li>
 Lead design and contribute to production Cloud / DevOps environments and Datalake, Data transformation, ETL/ELT jobs
 </li>
 <li>
 Experience of leveraging MS/Azure ecosystem to manage the development and maintenance of cloud platform operations
 </li>
 <li>
 A broad set of technical skills and knowledge across hardware, software, systems and solutions development
 </li>
 <li>
 A proven track record of using quantitative analysis to impact key business or product decisions
 </li>
 <li>
 Solid grasp of and experience with implementing and operating software development methodologies
 </li>
 <li>
 A solid grasp of common statistical applications and methods (A/B tests and multivariate experiments, probabilities, regression)
 </li>
 <li>
 Understanding of Agile Software Development Lifecycle and project planning/execution skills
 </li>
 <li>
 Outstanding communicating skills with stakeholders at all levels, managing stakeholders&rsquo; expectations and facilitate discussions across high risk or complexity or under constrained timescales.
 </li>
 <li>
 Outstanding capability to establish enterprise-scale data integration procedures across the data development life cycle and ensure that teams adhere to these. Able to manage resources to ensure that data services work effectively at an enterprise level.
 </li>
 <li>
 Up to date with data innovation and expert in investigating emerging trends in data-related approaches, performing horizon-scanning for the organisation and introducing innovative ways of working.
 </li>
 <li>
 Expert in Data integration design and can establish standards and well informed on best practice across different industries. The candidate can distinguish how to keep those standards up to date and ensures adherence to them.
 </li>
 <li>
 Good understanding of concepts and principles of data modelling and can produce, maintain and update relevant data models for specific business needs. Also, shows good knowledge on how to reverse-engineer data models from a live system.
 </li>
 <li>
 Expert in Metadata management and understands how metadata repositories can support different areas of the business. Capable of promoting and communicating the value of metadata repositories and knows how to set up robust governance processes to keep repositories up to date.
 </li>
 <li>
 Expert in identifying and anticipating problems and know how to prevent them by linking how problems fit into the larger picture. Has the ability to identify and describe problems and help others to describe them and knows how to build problem-solving capabilities in others.
 </li>
 <li>
 Expert in setting up team-based data engineering standards for programming tools and techniques and can select appropriate development methods. Act as an advisor on the application of standards and methods and ensure compliance and takes technical responsibility for all stages and/or iterations in a software development project, providing method-specific technical advice and guidance to project stakeholders.
 </li>
 <li>
 Technical Expert in predicting and advising on data engineering future technology changes that present opportunities for a product or programme.
 </li>
 <li>
 Experienced with reviewing requirements, specifications and defining test conditions with good understanding on how to identify issues and risks associated with work while being able to analyse and report test activities and results.
 </li>
 </ul>
 
 
 
 Agile/Digital Experience
 
 <ul>
 <li>
 Experience in Agile Development, with specific Data Engineer/Data Architect (or similar) experience preferred
 </li>
 <li>
 Understands relationship with Product Owner, Agile coach, Data Scientist, Designer and rest of technical team
 </li>
 </ul>
 
 
 
 Individual Skills
 
 <ul>
 <li>
 Exceptional problem-solving skills: demonstrated ability to understand business challenges,
 </li>
 <li>
 structure complex problems, develop solutions
 </li>
 <li>
 Ability to partner and influence key business stakeholders at all levels of the organization
 </li>
 <li>
 Strong skills in team leadership and networking, ability to work across multiple organizations to accomplish diverse goals
 </li>
 <li>
 Exceptional presentation, written, and verbal communication skills
 </li>
 <li>
 Strong communication skills with ability to align the organization on complex technical decisions
 </li>
 <li>
 Active coach and mentor whose goals are to grow and maximize the team&rsquo;s potential
 </li>
 <li>
 Strong ability and enthusiasm around data strategy and ability to inspire team and organization around the usage of data.
 </li>
 </ul>
</div>


Job Id: qyOlJoLldt15PPy/xzHVy0WBaAx0nZ0rVGN4HNuAy2iQb4d41RUns2YlY74hRON8z/VOingrTtDxxMM4hnA+Tdzc+Pgj5lwrvQ==

Head of Data Architecture

<div>
 
 
 Developing Future Leaders at EGA
 
 
 
 
 
 
 Emirates Global Aluminium is committed to nurturing emerging talent and preparing the next generation of professionals for impactful careers within the organisation. Our Graduate Trainee Program for UAE Nationals is designed to equip high-potential graduates with the skills, knowledge, and experience required to assume key roles in the future.
 
 
 
 
 
 
 Program Overview:
 
 
 <ol>
 <li>
 
 Structured Training &amp; Development.
 
 The program incorporates a blend of practical learning and leadership development, aimed at building the competencies necessary for the trainee's target position.
 </li>
 <li>
 
 Departmental Familiarisation.
 
 Trainees will gain broad exposure to their designated department, including an understanding of each section&rsquo;s core functions and responsibilities.
 </li>
 <li>
 
 18-Month On-the-Job Training.
 
 A focused training period that offers hands-on experience aligned with the trainee&rsquo;s intended role, supported by guidance from experienced professionals.
 </li>
 </ol>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 UAE Nationals with a Bachelor&rsquo;s Degree in
 
 Human Resources
 
 </li>
 <li>
 Strong interest in professional development and long-term career progression
 </li>
 <li>
 Demonstrated motivation, adaptability, and commitment to learning
 </li>
 </ul>
 
 
 
 
 This program represents a unique opportunity to contribute to one of the UAE&rsquo;s leading industrial organisations while developing the capabilities required for future leadership roles.
 
</div>


Job Id: u8KofqxwDklU/+EYBjUkB8EuC1R6rgxsqQQTmNeSzgudnuuWVkw/Mx0Vprd99wZwLFKx2dHEFWv9bvGe8CYG1kieaMlVKKs/VQ==

Graduate Trainee - Human Capital

Join Emirates Global Aluminium (EGA) and explore 3 exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.