1,196 Data Engineering jobs in Kenya

• Design, develop, and optimize large-scale data pipelines using ETL/ELT processes to ingest, transform, and load data from various sources.
• Build and maintain scalable data warehousing solutions and data lakes using modern cloud-based technologies (e.g., AWS, Azure, GCP).
• Implement data modeling best practices to ensure data integrity, consistency, and efficiency.
• Develop and maintain data quality frameworks and monitoring systems to ensure accuracy and reliability of data.
• Collaborate closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions.
• Develop and deploy machine learning models and analytical solutions by providing robust data infrastructure.
• Write efficient, well-documented, and maintainable code in languages such as Python, SQL, or Scala.
• Optimize query performance and data processing for large datasets.
• Ensure data security and compliance with relevant regulations.
• Stay abreast of emerging trends and technologies in big data, cloud computing, and data engineering.
• Mentor junior data engineers and contribute to the team's technical growth.

• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.
• Minimum of 6 years of professional experience in data engineering or a related role.
• Proven experience designing and building data pipelines for big data environments.
• Strong proficiency in SQL and programming languages such as Python or Scala.
• Hands-on experience with cloud data platforms (e.g., AWS Redshift, S3, Glue; Azure Data Factory, Databricks; Google BigQuery, Dataflow).
• Experience with distributed data processing frameworks like Spark or Hadoop.
• Solid understanding of data warehousing concepts, data modeling, and ETL/ELT best practices.
• Experience with containerization technologies (e.g., Docker, Kubernetes) is a plus.
• Excellent problem-solving, analytical, and communication skills.
• Ability to work effectively in a hybrid work environment, balancing remote and in-office responsibilities.
• Experience relevant to **Kakamega, Kakamega, KE** is a plus but not mandatory due to the hybrid nature.

A Business Data Analytics and Research intern plays a crucial role in organizations by leveraging data to drive strategic decision-making, conducting research to identify market trends, and optimizing business operations. Below are key responsibilities and skills typically associated with this role:

Key Responsibilities:

1. Data Collection and Analysis
   :

2. Gather and analyze business, market, and financial data from various sources to provide insights into performance and trends.

3. Use statistical tools to interpret data sets, identifying patterns and trends that inform business decisions.

2.Data Visualization, Reporting and Presentation
:

• Prepare and present detailed reports, dashboards, and visualizations that summarize key data insights and findings.
• Communicate complex data results to non-technical stakeholders in a clear and actionable manner.
• Capacity to develop concept notes and proposals based on market research gaps

3. Market Research
:

• Conduct qualitative and quantitative research to identify new market opportunities, competitor analysis, and customer preferences.
• Evaluate market conditions, industry trends, and competitors' activities to support business growth strategies.
• Prepare presentations based on market research reports

4.Business Performance Monitoring
:

• Monitor key performance indicators (KPIs) to track business progress and identify areas for improvement.
• Recommend improvements based on data insights to optimize processes, reduce costs, and increase profitability.

5.Collaborating with Teams
:

• Work closely with different departments such as marketing, finance, and operations to align data-driven insights with business objectives.
• Provide support for product development, sales strategies, and customer experience initiatives through data analysis.

6.Data Management
:

• Ensure the accuracy, completeness, and security of data.
• Develop and maintain databases, data collection systems, and strategies for efficient data storage and retrieval.

Key Skills:

1.Data Analytics Tools
:

• Proficient in tools like SQL, Excel, Tableau, Power BI, Google Analytics, and other business intelligence platforms.

2.Statistical Analysis
:

• Knowledge of statistical software (e.g., R, SAS, SPSS) and techniques such as regression analysis, hypothesis testing, and predictive modeling.

3.Research and Excellent Writing skills:

• Strong ability to conduct both primary and secondary research, including surveys, interviews, and literature reviews.
• Capacity to develop report and concepts based on market research reports

4.Problem-Solving
:

• Analytical thinking to identify issues, trends, and opportunities through data, and propose actionable solutions.

5.Communication Skills
:

• Excellent written and verbal communication skills to present findings and recommendations clearly to stakeholders.

6.Attention to Detail
:

• High level of precision in handling large data sets and ensuring data accuracy.

7.Project Management
:

• Ability to manage multiple research projects simultaneously, ensuring timely delivery of results.

Education, knowledge and experience:

• A degree in Agricultural Economics or a related field.
• Experience in management and analysis of data.
• Field experience and synthesis of data and lessons for learning
• Knowledge and savvy of data analysis software, especially Stata.
• Very strong analytical skills and applied statistical experience.
• Good scientific wring experience.

• Lead and conduct advanced scientific research in a designated field.
• Design, develop, and execute complex experiments and research protocols.
• Analyze and interpret large datasets, drawing meaningful conclusions.
• Develop and refine research methodologies and theoretical frameworks.
• Collaborate with internal and external research partners to advance projects.
• Prepare and present research findings through publications, reports, and presentations.
• Stay current with scientific literature, emerging technologies, and industry trends.
• Mentor and guide junior researchers and laboratory staff.
• Contribute to grant writing and funding acquisition efforts.
• Ensure adherence to ethical standards and safety protocols in research.

• Ph.D. in Chemistry, Biology, Physics, Materials Science, Computer Science, or a related scientific discipline.
• Minimum of 6 years of post-doctoral research experience.
• Demonstrated track record of innovative research and peer-reviewed publications.
• Expertise in specific research areas relevant to the client's needs.
• Proficiency in advanced laboratory techniques or computational modeling and simulation tools.
• Strong analytical, critical thinking, and problem-solving skills.
• Excellent written and verbal communication skills, with experience presenting complex data.
• Proven ability to lead research projects and work effectively in a remote team environment.
• Experience with data analysis software (e.g., R, Python, MATLAB) is highly desirable.
• Strong understanding of research ethics and scientific integrity.

• Assist senior analysts in collecting, cleaning, and organizing large datasets from various sources.
• Perform basic statistical analysis and data visualization to identify trends and patterns.
• Support the development of reports and presentations summarizing data findings for internal stakeholders.
• Help in the testing and validation of data models and analytical tools.
• Contribute to data quality assurance efforts, ensuring accuracy and integrity of datasets.
• Learn and apply new data analysis techniques and software under the guidance of experienced mentors.
• Participate in team meetings and brainstorming sessions, contributing fresh perspectives.
• Assist in the documentation of data processes, methodologies, and findings.
• Support ad-hoc data requests from different departments.
• Gain practical experience in SQL, Python or R for data manipulation and analysis.

• Recent graduate with a Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, Data Science, or a closely related quantitative field.
• Strong understanding of statistical concepts and data analysis principles.
• Proficiency in Microsoft Excel and a foundational knowledge of data visualization tools (e.g., Tableau, Power BI) is a plus.
• Familiarity with programming languages commonly used in data analysis such as Python or R is advantageous.
• Excellent attention to detail and a commitment to data accuracy.
• Strong analytical and problem-solving skills.
• Good written and verbal communication skills.
• Ability to work independently and collaboratively in a remote team setting.
• Enthusiasm to learn and a proactive attitude towards new challenges.
• Must be eligible to participate in an internship program.

• Alupe Kenya
• Posted 4 hours ago
• Deadline: 21 September 2025
• Partner: CIFOR-ICRAF

CIFOR-ICRAF
Share
This role is an integral part of CIMMYT's dryland legumes (groundnut, chickpea & pigeon pea) and cereals (sorghum & millets) breeding programs. The person hired will provide administrative support to enable timely planning and execution of activities, projects and initiatives for these breeding programs.

Duties and responsibilities

• Management of phenotyping nurseries and trials.
• Work closely with CIMMYT scientists and NARS implementing partners to ensure timely land preparation, seed assembly and planting of trials/nurseries according to the experimental design.
• Ensure proper agronomic management of trials like application of fertilizer, timely irrigation, weed and pest control
• Ensure disease/striga screening trials are artificially inoculated according to laid down procedures
• Ensure seeds for checks are available in sufficient quantities and when necessary increased in a timely manner
• Ensure pure pathogen cultures and striga seed are maintained in a viable state and available for artificial inoculation when needed.
• Data Collection and Organization.
• Manage accurate and timely data collection at different stages of the trials in the field, nurseries using the relevant tools and software
• Ensure accuracy of data entry and consolidation in preparation for analysis by the Scientists
• Learn and operate Enterprise Breeding System (EBS) for routine operations, data upload, data curation and preliminary analysis; basic familiarity with Breeding Management System (BMS) may be helpful.
• Supervise casual Labor.
• Develop budgets, and monitor budget utilization.
• Other Responsibilities.
• Assist partners based on their needs in coordination with the supervisor
• Establish and maintain contact with collaborating /implementing organizations and partners
• Any other task assigned by the supervisor.

Requirements

• BSc or MSc in Crop protection, agronomy or related Agricultural Sciences with at least 3 years accumulated practical experience in field trialing and management.
• Knowledge in managing agricultural field activities or research projects in a dynamic and fast paced organization.
• Thorough knowledge of field trials management, and field identification of biotic stresses affecting dryland crops.
• Familiarity with application of pest and disease evaluation scales especially of dryland crops.
• Ability to provide supervision and training to field staff to manage research activities
• Basic supervisory skills and experience are a must.
• Ability to communicate orally day-to-day matters and to prepare brief but accurate reports or complete forms without assistance.
• Ability to analyze situations or problems and timely propose or evaluate possible resolution mechanisms.
• Competency to use the standard Windows-based software for word processing, spreadsheets, presentations, and email used at CIMMYT.
• The selected candidate must exhibit the following competencies: Problem-solving and decision-making, negotiation and conflict resolution, communication, and teamwork.

Education, knowledge and experience

• BSc or MSc in Crop protection, agronomy or related Agricultural Sciences with at least 3 years accumulated practical experience in field trialing and management.
• Knowledge in managing agricultural field activities or research projects in a dynamic and fast paced organization.
• Thorough knowledge of field trials management, and field identification of biotic stresses affecting dryland crops.
• Familiarity with application of pest and disease evaluation scales especially of dryland crops.
• Ability to provide supervision and training to field staff to manage research activities
• Basic supervisory skills and experience are a must.
• Ability to communicate orally day-to-day matters and to prepare brief but accurate reports or complete forms without assistance.
• Ability to analyze situations or problems and timely propose or evaluate possible resolution mechanisms.
• Competency to use the standard Windows-based software for word processing, spreadsheets, presentations, and email used at CIMMYT.
• The selected candidate must exhibit the following competencies: Problem-solving and decision-making, negotiation and conflict resolution, communication, and teamwork.

Terms and conditions

• This is a Locally Recruited Staff (LRS) position and on competitive remuneration in local currency, commensurate with skills and experience.
• The appointment will be for two (2) years, including a six-month probationary period, with the possibility of extension contingent on performance, continued relevance of the position and available resources.
• The duty station will be in Alupe, Kenya.

Learn more

• Assist in gathering and preprocessing large, complex datasets from various sources.
• Perform exploratory data analysis to identify patterns, trends, and anomalies.
• Develop and implement statistical models and machine learning algorithms under guidance.
• Contribute to the design and execution of data-driven experiments.
• Visualize data and analytical results using various tools and techniques.
• Collaborate with senior data scientists and engineers to refine models and interpret findings.
• Document methodologies, findings, and code clearly and concisely.
• Stay up-to-date with the latest research and advancements in data science and machine learning.
• Participate in team meetings and contribute ideas for new analytical approaches.
• Support the development of data pipelines and analytical workflows.

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Strong understanding of statistical principles and machine learning concepts.
• Proficiency in at least one programming language commonly used in data science, such as Python or R.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Tableau).
• Excellent analytical and problem-solving skills.
• Strong communication skills, both written and verbal, with the ability to explain technical concepts to a non-technical audience.
• Eagerness to learn and adapt in a fast-paced, remote research environment.
• Previous internship or project experience in data science is a plus.
• Ability to work independently and manage time effectively in a remote setting.

• Lead and execute high-impact research projects in areas of chemical engineering and materials science.
• Conceptualize, design, and implement novel experiments to investigate complex phenomena.
• Develop new chemical synthesis routes, materials, and processes.
• Utilize advanced analytical techniques and instrumentation for characterization and testing.
• Analyze experimental data, interpret results, and draw meaningful conclusions.
• Publish research findings in peer-reviewed journals and present at scientific conferences.
• Mentor and guide junior research engineers and scientists.
• Collaborate with internal and external research partners.
• Identify and evaluate new research opportunities and technologies.
• Contribute to the strategic direction of the R&D department.

• Ph.D. in Chemical Engineering, Chemistry, Materials Science, or a closely related field.
• 10+ years of post-doctoral or industrial research experience with a strong track record of innovation.
• Demonstrated expertise in areas such as catalysis, polymer chemistry, nanotechnology, or process chemistry.
• Proven experience in experimental design, execution, and data analysis.
• Proficiency with advanced analytical and characterization techniques (e.g., spectroscopy, microscopy, chromatography).
• Excellent scientific writing and oral communication skills, with a history of impactful publications.
• Ability to think creatively and solve complex scientific problems.
• Strong leadership and mentoring capabilities.
• Experience working in a remote research environment is highly desirable.
• Self-motivated with the ability to work independently and manage multiple research projects.