Vacant Positions at First Quantum Minerals LTD

Purpose of the role:

This role will form part of a team of infrastructure engineers that overlook and provide critical (L3 and L4) support to data centres across multiple regions.

The incumbent shall form part of a talented team of engineers that demonstrate superb technical competency, delivering mission critical infrastructure and ensuring the highest levels of availability, performance and security.

The incumbent will provide expert technical assistance and expertise in performing capacity management and planning, evaluation of emerging infrastructure technologies, supporting data centre operations and a point of escalation for the different IT teams across multiple regions.

Key Responsibilities:

• Using in-depth knowledge of the supported platform (Microsoft – Hyper-V); recommends improvements, defines system solutions, defines process solutions, troubleshoots integration issues, and represents interests of the support team in enterprise systems portfolio planning.
• Ensures high availability of enterprise infrastructure platforms.
• Performs routine system monitoring, necessary troubleshooting and daily alert review, in order to determine the health and needs of systems.
• Maintains and recommends procedures for system administration activities, supports the development and maintenance of IT standards, and provides input for mid to long range systems planning.
• Designs and validates the hardware layer solutions, meeting resiliency and performance expectations.
• Maintains awareness and knowledge of industry technology trends for technical viability and risk management to the organisation.
• Adhere to and implement Group ICT standards and policies.
• Effectively and efficiently develop, maintain and optimise server infrastructure.

Qualifications Required:

• Bachelor degree in Computer Science or equivalent qualification(s)

Experience & Skills Required:

• A minimum of 5 years' experience managing high availability systems
• Must have experience in set-up/support of MS Hyper V Cluster environments
• Broad generalist knowledge of current, certified Information Technology standards, operating systems, and implications of emerging technology trends.
• Broad understanding of IT operational related technologies such as virtualisation, storage and backups.
• Database and Converged Architecture experience advantageous.
• Understanding of ITIL processes.
• Knowledge of in Cloud Technologies (Azure) would be advantageous.

Behavioural Traits Required:

• Ability to work well in a team
•  “First time fix” attitude
• Must be able to work in a globally diverse business environment
• Self-motivated
• Good interpersonal skills

Other Requirements:

• Required, at times, to be on-call and/or to work outside normal business hours and days of the week as necessary as we’re supporting 24/7 Mining Operations
• This is a hybrid based role with at least 1 day per week office attendance required

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Purpose of the Role:

• The Data Engineer will be responsible for designing, developing, and maintaining data pipelines and systems in the Azure cloud environment. The incumbent will work collaboratively within an integrated team of Data Engineering, Data Designers, Data Scientists, Database Administrators, DevOps Engineer and Data Architects. Together this integrated team ensures the smooth deployment and vigilant monitoring of data solutions.

Key Responsibilities:

Data Engineering:

Data acquisition & source management

• Develop and deploy efficient data pipelines using Azure Synapse Analytics, adhering to Medallion architecture principles, and ensuring alignment with Semantic layer concept.

Develop APIs & data feeds

• Extract, Transform, and Load (ETL) data from various sources (e.g., databases, APIs, flat files) into Azure data platforms.

Data Quality

• Ensure data quality and consistency during the ETL process.

Data Governance

• Implement and enforce data governance policies and security measures in compliance with industry standards and organizational requirements.
• Monitor and audit data access and usage to ensure data privacy and security.

Testing

• Work closely with cross-functional teams to design and implement automated testing strategies for Synapse resources.
• Participate in release management processes and coordinate deployments across different environments
• Monitor and manage build and deployment processes, troubleshoot issues, and implement improvements
• Ensure seamless deployment and monitoring of data solutions.
• Implement and manage CI/CD pipelines to streamline the deployment process.

Data Architecture:

Data Integration

• Contribute to integration standards for system to system requirements.
• Implement integrations with single sources of truth

Data Storage, transfer & access

• Maintain and set standards surrounding how data is stored, transferred and accessed in the data lake

Data Operations:

Monitor Data Products

• Leverage Parquet partitioning strategies to enhance data retrieval efficiency for optimal performance.
• Employ and optimise orchestration tools to guarantee timely availability of data in the necessary storage, while also minimizing any excess workload
• Monitor and fine-tune system performance for optimal efficiency.
• Utilize automation with utility templates to streamline data processing workflows.
• Optimise data storage and retrieval for performance and cost efficiency are maximized.

DevOps:

• Assist with develop, maintain, and optimize DevOps agent pipelines for Azure Synapse Analytics

Qualifications Required:

• Degree in Computer Science, Engineering, or related field.

Experience & Skills Required:

• At least 5 to 8 years’ experience. 
• Strong proficiency in Azure cloud services and tools, including Azure Synapse Analytics, and Medallion architecture.
• Minimum of 5 years’ hands-on experience in designing and implementing solutions using Common Data Model (CDM), demonstrating proficiency in data modelling and integration.
• Proficient in Scala or Pyspark for developing and optimizing data processing pipelines.
• Strong command of SQL for querying and manipulating structured data.
• Familiarity with Azure Stream Analytics.
• Familiarity with Azure Event Hubs.
• Experience with source control management systems like Git.
• Solid understanding of both streaming and batch data processing techniques, with a demonstrated ability to work with real-time and batch data pipelines.
• Experience with data governance, security, and compliance practices.
• In-depth knowledge of Parquet partitioning strategies for optimizing data retrieval performance.
• Proven experience in automating data processing workflows using utility templates.

Behavioural Traits Required:

• Performance and results orientated
• Collaborative team member and comfortable with duty rotation
• Effective communication abilities
• Proficiency in navigating change within an evolving environment
• Capability to perform effectively in high-pressure situations
• Exhibit leadership abilities, while also being adaptable to follow when necessary or step up to lead when required
• Knowledge and interest in computer systems and the latest technologies 

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Purpose of the role:

• First Quantum Minerals is a forward-thinking organization dedicated to leveraging data for informed decision-making and innovation. We are currently seeking an experienced Data Scientist with a minimum of 8 years' experience to join our dynamic team.
• The Data Scientist will play a pivotal role in various data-related responsibilities, with a primary focus on enhancing data-driven insights and value generation, and ensuring data adoption and compliance within the organization.

Key Responsibilities:

Common Data Model Development (Data Product Management)

• Conceptualising and executing initiatives that drive adoption, standardisation and value generation for the region.
• Accountable for regional data service desk and ensuring support queries are resolved.
• Leading a team of Data Designers who are responsible for data products and data operations.
• Collaborating with business stakeholders to align the data model/products with specific business requirements and use cases.
• Implementing version control mechanisms to manage changes to the data model/products over time.
• Identifying and recording how data maps from various sources to the common data model schema
• Continuously assessing and updating the common data model to accommodate evolving business needs and data sources.
• Communicating data model changes and updates to relevant stakeholders and ensuring a smooth transition.

Data Value Generation (Data Science)

• Extracting actionable insights and patterns from data using appropriate tools
• Performing data sampling to assess the quality and suitability of the data.
• Developing strategies for handling missing data, outliers, errors, and inconsistencies along with the data engineering teams.
• Choosing appropriate machine learning algorithms for project objectives.
• Designing the architecture of machine learning models, including neural network architectures if applicable.
• Deploying, maintain and improve machine learning models into production environments.

Data Adoption and Compliance

• Developing and executing strategies and standards for promoting data adoption within the organization.
• Monitor adoption/compliance of standards and best practices within areas/functions in the region.
• Ensuring data quality and reliability to boost user confidence and adoption.
• Monitoring and reporting on key adoption metrics, such as user engagement, data utilization, and user satisfaction.
• Implementing change management practices to facilitate the smooth adoption of new data-related technologies and processes.
• Providing support to stakeholders encountering issues or challenges in utilizing data resources effectively.
• Regularly communicating updates, successes, and challenges related to data adoption to the DNA Lead and project stakeholders.

Qualifications Required:

• Degree in a relevant field (e.g., Computer Science, Statistics, or a related field)

Experience & Skills Required:

• A minimum of 8 years of experience mining, manufacturing, or heavy industry roles.
• A minimum of 5 years' experience in data science or data analytics roles.
• A minimum of 2 years' experience in a leadership and stakeholder engagement roles.
• Proficiency in data science and machine learning tools and languages (e.g., Python, R, TensorFlow).
• Strong analytical, problem-solving, and communication skills.
• Experience in data governance, compliance, and data adoption strategies is a plus.

Behavioural Traits Required:

• Performance and Results Orientated
• Team player
• Effective Communication abilities
• Ability to manage change
• Ability to work under pressure
• Demonstrate leadership skills
• Knowledge and interest in computer systems and the latest technologies