Head of Data Architecture

About Emirates Global Aluminium

Emirates Global Aluminium is the world’s biggest ‘premium aluminium’ producer and the largest industrial company in the United Arab Emirates outside the oil and gas industry.  EGA is an integrated aluminium producer, with operations on four continents from bauxite mining to the production of cast primary aluminium and recycling. EGA employs over 7,000 of these people including more than 1,200 UAE Nationals. EGA operates aluminium smelters in Jebel Ali and Al Taweelah in the United Arab Emirates, an alumina refinery in Al Taweelah, a bauxite mine and associated export facilities in the Republic of Guinea, a speciality foundry in high strength recycled aluminium in Germany, and a recycling plant in the United States.

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’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:

• 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’s problems. This involves creating blueprints for data management systems to integrate, centralize, protect, and maintain the data sources.
• 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.
• Data Strategy: Contribute and support of EGA’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.
• Data Modelling & 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.
• 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.
• 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.
• 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.
• Communicate effectively complex data concepts, solutions, proposals in simple language to non-technical team members and senior leaders (Senior Director,C level, Executive Committee).
• 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.
• 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 & schema registries, data lineage and automation downstream.
• 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 & monitoring strategy, change request frame work and automation, scaling up and data partitioning strategy
• 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.

AUTHORITY/ DECISION MAKING:

• Design authority on data architecture, governance and technology selection to support scale up ambitions of 50-60 usecases a year.
• Validate data security protocols and resource allocation decisions based on usecase requirements.
• Validation of technical design and solutions to support 10 digital capabilities based on industry4.0 principles

QUALIFICATIONS & SKILLS:
Domain Expertise

• Bachelor’s degree required, MS or PhD preferred
• Bachelor’s in Data Science, Computer Science, Engineering, Statistics and 10+ years of relevant experience. 
• Minimum 10+ years of data architecture experience utilising strong leadership skills, including mentoring, communication, decision-making, and project management.
• 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
• Expert with batch and real-time processing frameworks (Apache Kafka, Apache Spark etc.) 
• Expert design knowledge and hands on experienceof designing data pipelines and workflow management tools like Airflow, relevant  NiFi, or Luigi.
• Expertise  of machine learning platforms and tools like TensorFlow, PyTorch, or scikit-learn.
• Data frameworks suitable for LLM’s
• Lead design and contribute to production Cloud / DevOps environments and Datalake, Data transformation, ETL/ELT jobs
• Experience of leveraging MS/Azure ecosystem to manage the development and maintenance of cloud platform operations
• A broad set of technical skills and knowledge across hardware, software, systems and solutions development
• A proven track record of using quantitative analysis to impact key business or product decisions
• Solid grasp of and experience with implementing and operating software development methodologies
• A solid grasp of common statistical applications and methods (A/B tests and multivariate experiments, probabilities, regression)
• Understanding of Agile Software Development Lifecycle and project planning/execution skills
• Outstanding communicating skills with stakeholders at all levels, managing stakeholders’ expectations and facilitate discussions across high risk or complexity or under constrained timescales.
• 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.
• 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. 
• 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.
• 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.
• 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.
• 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.
• 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. 
• Technical Expert in predicting and advising on data engineering future technology changes that present opportunities for a product or programme.
• 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.

 Agile/Digital Experience

• Experience in Agile Development, with specific Data Engineer/Data Architect (or similar) experience preferred
• Understands relationship with Product Owner, Agile coach, Data Scientist, Designer and rest of technical team

Individual Skills

• Exceptional problem-solving skills: demonstrated ability to understand business challenges,
• structure complex problems, develop solutions
• Ability to partner and influence key business stakeholders at all levels of the organization
• Strong skills in team leadership and networking, ability to work across multiple organizations to accomplish diverse goals
• Exceptional presentation, written, and verbal communication skills
• Strong communication skills with ability to align the organization on complex technical decisions
• Active coach and mentor whose goals are to grow and maximize the team’s potential
• Strong ability and enthusiasm around data strategy and ability to inspire team and organization around the usage of data

Mindset & Behaviors

• High energy and passionate individual who inspires teammates to reach their maximum potential
• Empathetic coach who can help to develop a new group of highly motivated data engineers
• Excited about trying new solutions outside standard approved
• Invested in developing a culture of trust, free thought and complete transparency