Training and Development


Data Science is becoming one of the most sought-after skills in today’s world, with the proliferation of data, and unfettered access to data there has been an increasingly demand for experts in data roles in most organization.

There is a dire need for business decisions to be timely, accurate, reliable, and valid. We are going to look at various data roles, and the impact those roles have in most organization. There has been some rhetoric’s around Job roles in Data Science which makes it unclear for those who want to choose a career path in data science.

To make some of this definition facile and define these roles clearly to avoid creating a pretty kettle of fish when faced with choices on which career path to adopt you need to understand the various roles and responsibilities.

Business Intelligence Developer

Business Intelligence Developer takes advantage of the business intelligence and data analytic software to translate data into information needed for business decision making. The information provided by a BI developer allows business users to spot trends in business data.




  • Data Modelling
  • Data Visualization
  • Communication and Problem-Solving Skills
  • Transform complex data into BI Solutions
  • Data warehousing

Job Roles

  • Gathering Business requirement needed for decision making
  • Identify business needs and proffer solutions from various data sources
  • Deploy, Design, and build new BI solutions that supports key decision making
  • Ensuring the design of High-quality BI reporting solutions (BI reports, dashboards, financial reports) based on teams standard and Processes
  • Managing large and complex data with expertise in design, Creation, management, and business use of large data volumes
  • Designing and building conceptual models
  • Data Aggregation and Dimensional Modelling
  • Establishing and maintaining relationship between Stakeholders
  • Understanding the Business Process and use BI technology to improve stakeholders business decisions
  • Providing tools and data for operational, tactical, and strategic decisions

Impact Value in the Organization

  • Delivering Information to Key audiences in the most dynamic, appropriate, and meaningful way
  • Improving the Quality and Accessibility of Visual reports
  • Develop and BI and Data Strategy, ensuring that business is robust, consistent, consolidated, and accessible reporting enviro
  • Develop leading Visual solutions to customers
  • Enterprise-wide solutions to bring improvements to decision-making across businesses
  • Build Customised reports for Business users

Business Intelligence Analyst

Business Intelligence Analyst (BI Analyst) helps organization transform business data necessary to make business decision. A BI Analyst clean, gather, analyze, interpret, share information about the business and highlights where necessary actions should be taken.


  • Data Visualization,
  • Knowledge of Python
  • Knowledge of aggregation Tool
  • Identify gaps in data
  • Business report automation


Advanced Excel, Python, Tableau, Power BI, Open Refine, JIRA, Microsoft SQL Server

Roles and Responsibilities

  • Experience in  developing and managing data systems to support decision making and managing information needs.
  • Knowledge of Extracting data across databases, cloud storage, and separate files within unstructured data.
  • Experience gathering business requirement and documenting  business process.
  • Working with Structured and Unstructured data.
  • Cleaning up Data from various data sources, and clean and combine them into Standardized formats.
  • Maintain report and analyse key operational sectors KPI’s, identifying risk, errors, issues, and improvement.

Impact in the Organization

  • Working with variety of stakeholders across the business to provide insights and spot relevant insight in the organization.
  • Aliasing with stakeholders of all levels, internal and external to ensure operational efficiency and value to end-end operating model
  • To help deliver data that supports business decisions.
  • Develop Insightful solutions to complex business problems

Data Analyst/ Data Analytics Manager

Data Analyst collect data from various data sources/business system and then cleanse them, analyse, interpret, and answer business questions. Data Analysis creates an environment to glean insights from data to make business decisions.


Data Modelling

Data Mapping

Data Warehousing

Business Reporting



Power BI, Excel, Google Analytics, Tableau, Support VBA, Microsoft Access, MSBI(SQL, SSRS, SSIS),Microsoft Corporations SQL, QlikView, ETL

Roles and Responsibilities

  • Formulate Business Problems into hypothesis for analysis, utilising innovating technique
  • Generate reports, dashboard, graphs, and visualization that showcase data in an easy-to-understand format
  • Working with customer and delivery teams, in compiling and collating information from various data sources for structured and unstructured data.
  • Identify, collect, and migrate data from range of systems
  • Manage, Clean, abstract, and aggregate data alongside a range of analytical studies
  • Support the business in its transition from descriptive, to predictive, to prescriptive
  • Implement Data Analysis and other initiatives, that optimize data quality and process efficiencies for the bank.
  • Experience in Database management (maintenance, manipulation, access, and query) using SQL
  • Expertise in Database modelling, reporting, analysis, and presentations

Impacts and Values in the Organization

  • Improved decision-making process that will improve income and increase service delivery
  • Provide high level requirement elicitation to ensure development and management of data solutions
  • Helping organizations make better use of data for decision making to drive customer’s interactions
  • Translate and communicate accurate information to technical and non-technical stakeholders
  • Using Advanced Analytics to develop business solutions to with increase understanding of the business.

Data Scientist

Data Scientist are specialist who deal with Big data usually messy unstructured data from social media feeds, smart devices, e-commerce, reviews, community and situations where they don’t fit in the database They have technical skills to help solve complex business problems.

A data scientist must have a strong background computer science, statistics, and Mathematics.

Skills– Python, Java, SQL, R,  Python ML Stack (SciPy, Pandas, NumPy)  Alteryx SQL, Object Oriented Programming.


Tableau, Power BI, AZURE, Data Bricks.

Roles and Responsibilities

  • Developing and Deploying AI/ML Solutions that leverage our business (BSS)
  • Build validation of advanced models/algorithm to solve core customer issues
  • Enable cost-effective design, development, test, optimisation, deployment of data solutions
  • Exposure to working with complex and messy data sets.
  • Collaborate with Machine Language Engineers, ML operations (MLOPS), data engineers, and IT to evaluate and Implement ML deployment options
  • Strong knowledge and experience of project managements methodologies: include Agile methodologies, and hypothesis-driven approach

Impact Value in the Organization

  • Build and Design Algorithm to Improve Decision Making.
  • Innovating and developing Data Products that drive revenue, operational revenue, operational efficiencies or risk/fraud detections.

Database Administrator

Database Administrator is a person who manages, maintains, and secures the organizations database and other data assets. The Database Administrator creates an environment where business users can perform analysis for business operations.


  • Performance Monitoring and Tuning
  • T-SQL Scripting
  • Database Migration
  • Database Design.


MS SQL Environment, SQL Server (Technical Experience), Oracle Databases , Azure PAAS, Window Server, Microsoft SSIS, SSAS, SSRS.

Roles and Responsibility

  • Experience of Database Applications and Server Performance Tuning
  • Monitoring Database Activities for optimum performance, security, and Integrity
  • Installation, Configurations, backup, recovery & Refresh of Database
  • Maintenance of User accounts, auditing, and permissions to ensure data quality
  • Documents organizations database environment
  • SQL server maintenance, scheduling, and alerting
  • Administering SQL in a Virtual environment

Impact Values in the Organization

  • To provide support to existing database infrastructure which includes updates, patching, deployment, monitoring, as well as project-based work
  • Provide supports for Internal and external developers in deploying new services, and website into productions

Data Engineers

Data Engineers build pipelines needed to transform raw unstructured data into format data scientist can use for analysis. They are responsible for creating and maintaining the analytics infrastructure that enables every other data to function. They are responsible for transforming data into staging area and loading in a data warehouse system referred to as ETL ( Extract, Transform, and Load)


  • Build Data Pipelines
  • Data Modelling
  • Building Data Warehouse
  • SQL Scripting
  • Machine Learning


AWS, Power BI, Synapse, Azure Data Factory, Azure Data Bricks, Azure Data Engineering,


  • Develop and Deploy machine model, into Production System.
  • Implement rest API’s and working with wider Product & Technology team to ensure end-end Product delivery.
  • Experience building, interpreting, and present applications and machine learning modelling and statistical techniques
  • Support existing data warehouse and solution, to ensure they remain fit for purpose and performant.
  • Develop consistent technical builds, implementation and support processes.
  • Building automated ETL pipelines, that are easy to maintain, are scalable and secure.
  • Collaborate with Cross functional team which includes Data Strategist, Data Scientist, and business stakeholders
  • Deep experience in Schema design, and dimensional Data modelling
  • Perform accurate data mining and extraction from relevant structured and unstructured sources to provide insights and MI
  • Hands on experience on database design.


  • Contribute to the development and management of the engineering teams’ processes
  • Ensure the consistent development of high-quality, clean, and performant code, with operability
  • Help client’s deploy data pipelines and processes in a production safe-manner, using the latest technology.


A data architect is someone who defines the organization strategy, which includes creating an integrated framework for standard of quality, the data flow across the organization, and security of data. A Data Architect has a clear understanding of business needs, aligns with the strategic requirement of the organization and related business architecture.



Dimensional Data Model

Database Design


Enterprise Data Architecture

Data Modelling

Big Data



AWS, Azure, Data Bricks, Sparks, Power BI, SQL Server, SAP Business Object, Synapse Analytics, Delta Lake, Data Modelling, Data Migration, TOGAF.

Roles and Responsibilities

  • Develop and maintain architectural blueprint, target operating models, and roadmap
  • Architect and Design Solutions to meet functional and non-functional requirement
  • Data Migration and the ability to be consulted with data movement for data performance and optimization.
  • Designing Cloud Solutions and Incorporating information securities principle and best practice designs to ensure with regulatory data security and data governance principle.
  • Architecture design patterns guiding operational management and best practices


The data architect owns and maintains data flow, data dictionaries, and data models along with the enterprise information architecture.

Architecting and Developing solutions for Business customers



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