Specialist Data Engineer
2025-07-31T12:05:29+00:00
Absa Bank
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https://www.absa.co.ug/personal/
FULL_TIME
Nairobi
Nairobi
00100
Kenya
Banking
Computer & IT
2025-08-07T17:00:00+00:00
Kenya
8
Job Description
Data Architecture & Data Engineering
- Understand the technical landscape and bank wide architecture that is connected to or dependent on the business area supported in order to effectively design & deliver data solutions (architecture, pipeline etc.)
- Translate / interpret the data architecture direction and associated business requirements & leverage expertise in analytical & creative problem solving to synthesise data solution designs (build a solution from its components) beyond the analysis of the problem
- Participate in design thinking processes to successfully deliver data solution blueprints
- Leverage state of the art relational and No-SQL databases as well integration and streaming platforms do deliver sustainable business specific data solutions.
- Design data retrieval, storage & distribution solutions (and OR components thereof) including contributing to all phases of the development lifecycle e.g. design process
- Develop high quality data processing, retrieval, storage & distribution design in a test driven & domain driven / cross domain environment
- Build analytics tools that utilize the data pipeline by quickly producing well-organised, optimized, and documented source code & algorithms to deliver technical data solutions
- Create & Maintain Sophisticated CI / CD Pipelines (authoring & supporting CI/CD pipelines in Jenkins or similar tools and deploy to multi-site environments – supporting and managing your applications all the way to production)
- Automate tasks through appropriate tools and scripting technologies e.g. Ansible, Chef
- Debug existing source code and polish feature sets.
- Assemble large, complex data sets that meet business requirements & manage the data pipeline
- Build infrastructure to automate extremely high volumes of data delivery
- Create data tools for analytics and data science teams that assist them in building and optimizing data sets for the benefit of the business
- Ensure designs & solutions support the technical organisation principles of self-service, repeatability, testability, scalability & resilience
- Apply general design patterns and paradigms to deliver technical solutions
- Inform & support the infrastructure build required for optimal extraction, transformation, and loading of data from a wide variety of data sources
- Support the continuous optimisation, improvement & automation of data processing, retrieval, storage & distribution processes
- Ensure the quality assurance and testing of all data solutions aligned to the QA Engineering & broader architectural guidelines and standards of the organisation
- Implement & align to the Group Security standards and practices to ensure the undisputable separation, security & quality of the organisation’s data
- Meaningfully contribute to & ensure solutions align to the design & direction of the Group Architecture & in particular data standards, principles, preferences & practices. Short term deployment must align to strategic long term delivery.
- Meaningfully contribute to & ensure solutions align to the design and direction of the Group Infrastructure standards and practices e.g. OLA’s, IAAS, PAAS, SAAS, Containerisation etc.
- Monitor the performance of data solutions designs & ensure ongoing optimization of data solutions
- Stay ahead of the curve on data processing, retrieval, storage & distribution technologies & processes (global best practices & trends) to ensure best practice
Risk & Governance
- Identify technical risks and mitigate these (pre, during & post deployment)
- Update / Design all application documentation aligned to the organization technical standards and risk / governance frameworks
- Create business cases & solution specifications for various governance processes (e.g. CTO approvals)
- Participate in incident management & DR activity – applying critical thinking, problem solving & technical expertise to get to the bottom of major incidents
- Deliver on time & on budget (always)
Must have experience in:
- Spark and Scala Developers
- Hadoop experience
- Experience in ETL
- AWS (S3 Buckets)
- Data Engineering skill
Data Architecture & Data Engineering Understand the technical landscape and bank wide architecture that is connected to or dependent on the business area supported in order to effectively design & deliver data solutions (architecture, pipeline etc.) Translate / interpret the data architecture direction and associated business requirements & leverage expertise in analytical & creative problem solving to synthesise data solution designs (build a solution from its components) beyond the analysis of the problem Participate in design thinking processes to successfully deliver data solution blueprints Leverage state of the art relational and No-SQL databases as well integration and streaming platforms do deliver sustainable business specific data solutions. Design data retrieval, storage & distribution solutions (and OR components thereof) including contributing to all phases of the development lifecycle e.g. design process Develop high quality data processing, retrieval, storage & distribution design in a test driven & domain driven / cross domain environment Build analytics tools that utilize the data pipeline by quickly producing well-organised, optimized, and documented source code & algorithms to deliver technical data solutions Create & Maintain Sophisticated CI / CD Pipelines (authoring & supporting CI/CD pipelines in Jenkins or similar tools and deploy to multi-site environments – supporting and managing your applications all the way to production) Automate tasks through appropriate tools and scripting technologies e.g. Ansible, Chef Debug existing source code and polish feature sets. Assemble large, complex data sets that meet business requirements & manage the data pipeline Build infrastructure to automate extremely high volumes of data delivery Create data tools for analytics and data science teams that assist them in building and optimizing data sets for the benefit of the business Ensure designs & solutions support the technical organisation principles of self-service, repeatability, testability, scalability & resilience Apply general design patterns and paradigms to deliver technical solutions Inform & support the infrastructure build required for optimal extraction, transformation, and loading of data from a wide variety of data sources Support the continuous optimisation, improvement & automation of data processing, retrieval, storage & distribution processes Ensure the quality assurance and testing of all data solutions aligned to the QA Engineering & broader architectural guidelines and standards of the organisation Implement & align to the Group Security standards and practices to ensure the undisputable separation, security & quality of the organisation’s data Meaningfully contribute to & ensure solutions align to the design & direction of the Group Architecture & in particular data standards, principles, preferences & practices. Short term deployment must align to strategic long term delivery. Meaningfully contribute to & ensure solutions align to the design and direction of the Group Infrastructure standards and practices e.g. OLA’s, IAAS, PAAS, SAAS, Containerisation etc. Monitor the performance of data solutions designs & ensure ongoing optimization of data solutions Stay ahead of the curve on data processing, retrieval, storage & distribution technologies & processes (global best practices & trends) to ensure best practice Risk & Governance Identify technical risks and mitigate these (pre, during & post deployment) Update / Design all application documentation aligned to the organization technical standards and risk / governance frameworks Create business cases & solution specifications for various governance processes (e.g. CTO approvals) Participate in incident management & DR activity – applying critical thinking, problem solving & technical expertise to get to the bottom of major incidents Deliver on time & on budget (always)
Spark and Scala Developers Hadoop experience Experience in ETL AWS (S3 Buckets) Data Engineering skill
No Requirements
JOB-688b5c094abb6
Vacancy title:
Specialist Data Engineer
[Type: FULL_TIME, Industry: Banking, Category: Computer & IT]
Jobs at:
Absa Bank
Deadline of this Job:
Thursday, August 7 2025
Duty Station:
Nairobi | Nairobi | Kenya
Summary
Date Posted: Thursday, July 31 2025, Base Salary: Not Disclosed
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JOB DETAILS:
Job Description
Data Architecture & Data Engineering
- Understand the technical landscape and bank wide architecture that is connected to or dependent on the business area supported in order to effectively design & deliver data solutions (architecture, pipeline etc.)
- Translate / interpret the data architecture direction and associated business requirements & leverage expertise in analytical & creative problem solving to synthesise data solution designs (build a solution from its components) beyond the analysis of the problem
- Participate in design thinking processes to successfully deliver data solution blueprints
- Leverage state of the art relational and No-SQL databases as well integration and streaming platforms do deliver sustainable business specific data solutions.
- Design data retrieval, storage & distribution solutions (and OR components thereof) including contributing to all phases of the development lifecycle e.g. design process
- Develop high quality data processing, retrieval, storage & distribution design in a test driven & domain driven / cross domain environment
- Build analytics tools that utilize the data pipeline by quickly producing well-organised, optimized, and documented source code & algorithms to deliver technical data solutions
- Create & Maintain Sophisticated CI / CD Pipelines (authoring & supporting CI/CD pipelines in Jenkins or similar tools and deploy to multi-site environments – supporting and managing your applications all the way to production)
- Automate tasks through appropriate tools and scripting technologies e.g. Ansible, Chef
- Debug existing source code and polish feature sets.
- Assemble large, complex data sets that meet business requirements & manage the data pipeline
- Build infrastructure to automate extremely high volumes of data delivery
- Create data tools for analytics and data science teams that assist them in building and optimizing data sets for the benefit of the business
- Ensure designs & solutions support the technical organisation principles of self-service, repeatability, testability, scalability & resilience
- Apply general design patterns and paradigms to deliver technical solutions
- Inform & support the infrastructure build required for optimal extraction, transformation, and loading of data from a wide variety of data sources
- Support the continuous optimisation, improvement & automation of data processing, retrieval, storage & distribution processes
- Ensure the quality assurance and testing of all data solutions aligned to the QA Engineering & broader architectural guidelines and standards of the organisation
- Implement & align to the Group Security standards and practices to ensure the undisputable separation, security & quality of the organisation’s data
- Meaningfully contribute to & ensure solutions align to the design & direction of the Group Architecture & in particular data standards, principles, preferences & practices. Short term deployment must align to strategic long term delivery.
- Meaningfully contribute to & ensure solutions align to the design and direction of the Group Infrastructure standards and practices e.g. OLA’s, IAAS, PAAS, SAAS, Containerisation etc.
- Monitor the performance of data solutions designs & ensure ongoing optimization of data solutions
- Stay ahead of the curve on data processing, retrieval, storage & distribution technologies & processes (global best practices & trends) to ensure best practice
Risk & Governance
- Identify technical risks and mitigate these (pre, during & post deployment)
- Update / Design all application documentation aligned to the organization technical standards and risk / governance frameworks
- Create business cases & solution specifications for various governance processes (e.g. CTO approvals)
- Participate in incident management & DR activity – applying critical thinking, problem solving & technical expertise to get to the bottom of major incidents
- Deliver on time & on budget (always)
Must have experience in:
- Spark and Scala Developers
- Hadoop experience
- Experience in ETL
- AWS (S3 Buckets)
- Data Engineering skill
Work Hours: 8
Experience: No Requirements
Level of Education: bachelor degree
Job application procedure
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