Data Analytics engineer

Job summary

A Data Analytics Engineer is responsible for the administration, optimization, security, and analysis of enterprise databases, as well as developing business intelligence, reporting, and data-driven decision-making for the Company's Customers. The role combines: Database Administration (DBA), Advanced SQL Development, Data Analytics, Business Intelligence Reporting, and Data Engineering. The successful candidate will play a key role in ensuring the availability, integrity, performance, and reliability of data systems, while developing insightful dashboards and analytics solutions to support customer decision-making.

Key Responsibilities**

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SQL Development & Data Engineering

• Advanced SQL Development

• Develop and maintain:

• Complex SQL scripts

• Stored procedures

• Database functions

• Views

• ETL processes

• Batch processing scripts

Query Optimization

_Write and optimize:_

• Complex SELECT statements

• JOIN operations

• Window functions

• Common Table Expressions (CTEs)

• Dynamic SQL queries

Data Automation

_Develop automated processes for:_

• Data synchronization

• Scheduled reporting

• Data validation

• Data cleansing

• Reporting pipelines

Data Warehousing Support

_Assist in:_

• Data warehouse development

• Data transformation

• Data mart creation

• Aggregation and analytics structures

Data Analytics & Business Intelligence

_Data Analysis_

• Analyze operational and transactional data to identify:

• Trends

• Patterns

• KPIs

• Exceptions

• Risk indicators

Dashboard & Reporting

_Develop and maintain dashboards and reports using the Company’s BI tool:_

To develop:

• Executive dashboards

• KPI scorecards

• Operational reports

• Drill-down analytics reports

• Trend and performance reports

Business Intelligence Support

• Design and maintain:

• Star schemas

• Dimensional models

• Data marts

• Reporting structures

Data Quality & Governance

_Data Quality Management_

• Implement and monitor:

• Data validation rules

• Duplicate detection

• Data consistency checks

• Data cleansing processes

_Data Governance_

Maintain:

• Data standards

• Naming conventions

• Metadata documentation

• Data structure documentation

Requirements

Required Qualifications

• Bachelor’s Degree in: Computer Science, Information Technology, Statistics and Data Science, or related field

• Minimum of 2–5 years’ experience in database administration, SQL development, or data analytics.

• Professional certifications in SQL Server, PostgreSQL, Power BI, or Data Analytics will be an added advantage.

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Required Technical Skills:

Database Technologies

• Microsoft SQL Server

• PostgreSQL

• Oracle Database (advantage)

SQL & Database Skills

Strong knowledge in:

• SQL scripting

• Query optimization

• Stored procedures

• Triggers

• Views

• Functions

• Database indexing

• Performance tuning

• Backup and recovery

Analytics & BI Skills

• Power BI

• Tableau

• Data modeling

• Dashboard development

• KPI reporting

• Statistical and trend analysis

Data Engineering Skills

• ETL development

• Data transformation

• Data warehousing

• API integrations

Soft Skills

• Strong analytical and problem-solving skills

• Excellent attention to detail

• Good communication and presentation skills

• Ability to work independently and within teams

• Strong business and reporting mindset

• Ability to explain technical information to non-technical users

• Creativity and innovation

• Goal-oriented mindset

• Ability to work under pressure and meet targets

Key Performance Indicators (KPIs):

Performance for this role will be measured using:

• Database up time and availability

• Query performance optimization

• Report and dashboard delivery timelines

• Data accuracy and quality levels

• Reduction in data inconsistencies

• Efficiency of analytics reporting

• Customer satisfaction with reports and dashboards

Ideal Candidate Profile

The ideal candidate should:

• Have strong SQL scripting and database administration skills.

• Be highly analytical and business oriented.

• Be capable of translating data into actionable business insights.

• Understand enterprise systems and reporting environments.

• Be proactive in identifying opportunities, trends, and operational risks through data analysis.

• Have experience working with business intelligence and analytics tools.

Benefits

Salary: GHS 4,000 - GHS 5,000

Other Benefits: SSNIT, 13th Month Salary, & Performance Incentives