Title:  Junior Analytics Engineer

Job Purpose

To determine strategic and enterprise business insights through analysing business processes, analysing data flows, mining data, defining measurement goals and storyboarding.

Job Responsibilities

• Design Data and Conceptual Modelling
  • Has a basic understanding of business data and information requirements, the related data flow, business processes and systems that generate the data required as well as the properties, profile and behaviour of the data.
  • Collaborate with various teams including Data Modelers, Data Engineers, Data Architects and Data Governance to align data discovery insights and implement basic data solutions.
  • Liaise with business stakeholders to elicit and understand data requirements.
  • Has a basic understanding of data, relational and dimensional modelling concepts.
  • Monitor and check that data lineage is available.
• Data Architecture
  • Assist in building and maintaining data architecture models, schemas, and metadata within the scalable data architecture, following standards and documenting changes to support efficient storage, retrieval, and analysis.
  • Consult and educate stakeholders on methods for streamlining and standardising data collection to ensure quality and accuracy.
•  Databases Specifications
  • Provide information on suitability during the approval process for database specifications to ensure all agreed standards and protocols are followed and data integrity is preserved.
  • Perform basic data testing and validation activities such as error resolution and data quality validation end to end through the data lifecycle.
• Databases Installation
  • Has a basic understanding of how data pipelines are built.
  • Monitor data pipelines and infrastructure to provide first line support, resolve issues and ensure that the data product meets its SLA timelines for data availability and reliability.
• Data Protection
  • Ensure that all work adheres to regulatory requirements, maintaining compliance with all relevant data policies, privacy standards, and ownership guidelines.

Essential Requirements:

• Undergraduate Degree
• General Experience: Experienced practitioner able to work unsupervised (1 to 3 years)

Technical Expertise

• Enabling Self-Service Insights: Works at an intermediate level to create intuitive, governed data models and metrics, document them and empower stakeholders to self-serve insights. Typically works with guidance.
• Build Data Products: Works at an intermediate level to create reliable datasets/metrics/APIs, document and permission them, deploy to users, monitor and improve. Typically works with guidance.

• Design Data Products: Works with full competence to discover user needs, define value and outcomes, specify data contracts, success metrics and plan the roadmap. Typically works without supervision and may provide technical guidance.
• Data Visualisation: Works with full competence to select the best data visualising tools to create accessible and accurate visuals and to turn these into a clear narrative, highlighting what matters and guide decisions. Typically works without supervision and may provide technical guidance.
• Data Governance Principles: Works at an intermediate level to manage data in accordance with the organisation's data governance protocols, including sourcing, handling, classifying, storing, monitoring, extracting, loading, transporting and securing relevant data, while understanding and applying data quality principles to enhance the accuracy, consistency, and reliability of organisational data. Typically works with guidance.
• Business Data Modelling: Works at an intermediate level to conduct activities to collect, analyse, diagram (model) and report information and data flow, including state changes, to help make strategic decisions, achieve major goals, and solve complex problems. Typically works with guidance.

Behavioural competencies

• Collaborates: Builds partnerships and works collaboratively with others to meet shared objectives. For example, readily involves others to accomplish goals; stays in touch and shares information; discourages "us versus them" thinking; shows appreciation for others' ideas and input.
• Ensures Accountability: Holds self and others accountable to meet commitments. For example, accepts responsibility for own work, both successes and failures. Handles fair share and does not make to others.
• Optimises Work Processes: Knows the most effective and efficient processes to get things done, with a focus on continuous improvement. For example, uses metrics and benchmarks to monitor accuracy and quality. Takes steps to make methods productive and efficient. Promptly and effectively addresses process breakdowns.
• Decision Quality: Makes good and timely decisions that keep the organisation moving forward. For example, knows when to act independently and when to escalate issues. Integrates various inputs, decision criteria, and trade-offs to make effective decisions. Typically makes good independent decisions.
• Manages Complexity: Makes sense of complex, high quantity, and sometimes contradictory information to effectively solve problems. For example, looks at complex issues from multiple angles; explores issues to uncover underlying issues and root causes; sees the main consequences and implications of different options.