494 Big Data jobs in Kenya

• Assist in collecting, cleaning, and organizing large datasets from various sources.
• Perform basic data analysis using statistical methods and tools.
• Help develop reports and dashboards to visualize data and communicate findings.
• Support senior analysts in identifying trends, patterns, and insights within the data.
• Learn and apply data querying languages such as SQL.
• Participate in team meetings and contribute to project discussions.
• Assist in the development and maintenance of data models.
• Follow established data governance and quality standards.
• Collaborate with cross-functional teams to understand data needs.
• Actively engage in training and skill development opportunities.

• A degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or a related discipline, or equivalent demonstrable aptitude.
• Strong analytical and problem-solving skills.
• Proficiency with spreadsheet software (e.g., Microsoft Excel).
• Basic understanding of programming concepts and willingness to learn languages like SQL, Python, or R.
• Excellent attention to detail and organizational skills.
• Good communication and teamwork abilities.
• Eagerness to learn and develop skills in data analysis and big data technologies.
• Ability to work independently and manage tasks in a remote setting.

• Design, develop, and implement highly scalable and reliable data pipelines for batch and real-time data processing.
• Build and maintain robust ETL/ELT processes using modern data warehousing techniques.
• Optimize data storage and retrieval for performance and cost-efficiency on cloud platforms (AWS, GCP, or Azure).
• Collaborate with data scientists and analysts to ensure data availability and quality for analytical models and reporting.
• Develop and manage data infrastructure, ensuring security, compliance, and reliability.
• Implement data governance policies and procedures.
• Troubleshoot and resolve issues related to data pipelines and infrastructure.
• Stay abreast of emerging technologies in big data and data engineering, and recommend their adoption.
• Mentor junior data engineers and contribute to a culture of technical excellence.
• Participate in code reviews and contribute to architectural design discussions.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• 5+ years of experience in data engineering, with a strong focus on big data technologies.
• Proficiency in programming languages such as Python, Scala, or Java.
• Extensive experience with distributed data processing frameworks like Apache Spark, Hadoop, Flink.
• Deep understanding of SQL and NoSQL databases.
• Experience with cloud data services (e.g., AWS S3, Redshift, EMR; Google Cloud Storage, BigQuery, Dataproc; Azure Data Lake, Synapse Analytics).
• Familiarity with workflow management tools like Airflow.
• Experience with data warehousing concepts and best practices.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities, particularly in a remote team setting.

• Assist in collecting, cleaning, and pre-processing large datasets from various sources.
• Perform exploratory data analysis to identify trends, patterns, and anomalies.
• Support the development of dashboards and reports to visualize data insights for stakeholders.
• Collaborate with senior data analysts and data scientists on ongoing projects.
• Learn and apply statistical methods and data mining techniques.
• Document data analysis processes and findings.
• Contribute to the maintenance and improvement of data quality and integrity.
• Participate in team meetings and provide updates on assigned tasks.
• Assist in testing and validating data models and analytical outputs.
• Help in preparing presentations that communicate complex data findings in a clear and concise manner.

• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline.
• Basic understanding of statistical concepts and data analysis principles.
• Familiarity with data analysis tools and programming languages such as Python (Pandas, NumPy) or R is a plus.
• Experience with SQL for data querying is advantageous.
• Strong analytical and problem-solving skills.
• Excellent attention to detail and organizational abilities.
• Good communication and collaboration skills, essential for a remote team.
• Ability to learn quickly and adapt to new technologies and methodologies.
• A genuine interest in data and its potential to drive business decisions.

• Design, build, and optimize scalable data pipelines and ETL/ELT processes.
• Develop and manage robust data warehousing and data lake solutions.
• Lead the architecture and implementation of big data platforms and infrastructure.
• Ensure data quality, integrity, and security across all data systems.
• Collaborate with data scientists and analysts to provide them with reliable data access.
• Mentor and guide junior data engineers, fostering their technical growth.
• Evaluate and recommend new technologies and tools to enhance data capabilities.
• Monitor system performance, troubleshoot issues, and implement solutions for optimization.
• Develop and enforce data governance policies and standards.
• Drive innovation in data engineering practices and methodologies.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Minimum of 8 years of experience in data engineering, with at least 2 years in a lead or senior role.
• Extensive experience with cloud platforms (AWS, Azure, or GCP) and their data services.
• Deep expertise in big data technologies such as Apache Spark, Hadoop, Kafka, and related ecosystems.
• Proficiency in programming languages like Python, Scala, or Java.
• Strong SQL skills and experience with various database technologies (relational and NoSQL).
• Experience with data modeling and schema design.
• Excellent leadership, communication, and problem-solving skills.
• Ability to manage remote teams and projects effectively.
• A passion for building high-performance data infrastructure.

Our client is a multinational financial services firm, with a significant footprint.

Based in either Nairobi or Kuala Lumpur, this role will play a critical role in supporting their internal audit activities by providing insights through the analysis and correlation of data extracted from various systems across the business. Through advanced data analytics techniques, the role will enable the audit team to identify control failures, assess risks, and provide independent assurance to senior leadership that risks are being managed effectively and remain within the organization's approved risk appetite.

Key analytical activities include:

• Data profiling:
  Generating statistics to provide context and background on business processes.
• Reperformance testing:
  Re-performing calculations to validate transactions (e.g., payroll, claims), metrics from management information reports, and analytics models.
• Exception detection:
  Identifying instances where known restrictions, policies, or guidelines have not been followed.
• Anomaly detection:
  Detecting unusual or unexpected patterns of behaviour through data analysis.
• Root cause analysis:
  Identifying and quantifying the factors contributing to control failures and providing actionable insights.

The role also supports the internal audit leadership team in assessing the overall effectiveness of risk management practices.

Scope of the Role

As part of the regional audit resource pool, the Data Analytics Manager will be responsible for:

• Applying data analytics tools such as
  SQL
  and
  Python
  to support audit teams across the full audit lifecycle, from planning through closure.
• Detecting symptoms of control failures by analyzing operational data and providing insights to audit leads.
• Developing and maintaining
  continuous auditing dashboards
  using visualization tools such as
  Tableau
  or
  Power BI
  , providing clear visibility of control effectiveness across business units.
• Identifying trends and emerging themes that support the development of opinions on the organization's overall control environment.
• Supporting leadership in delivering continuous improvement initiatives and meeting stakeholder reporting requirements.
• Collaborating with internal teams, including
  IT
  and
  Compliance
  , to facilitate efficient data sourcing for audits and analytics initiatives.

Key Accountabilities

• Build and maintain strong working relationships with audit directors, internal audit leadership, and operational management teams.
• Deliver analytics outputs in line with internal methodologies and audit timelines.
• Provide audit leads with timely, accurate data-driven insights during fieldwork.
• Present audit findings to senior management, ensuring that appropriate responses are obtained for each identified issue.
• Manage analytics projects effectively, taking ownership of deliverables from start to finish.

Core Competencies

• Strong technical skills with
  SQL
  and
  Python (Pandas Library)
  for data analytics.
• Proficiency in visualization tools such as
  Tableau
  and/or
  Power BI
  .
• Advanced knowledge of
  Python
  /
  R
  for text analytics, NLP, predictive analytics, or machine learning is highly desirable.
• Excellent stakeholder management, communication, and presentation skills.

Knowledge & Experience

• Hands-on technical experience
  mining, cleaning, and analyzing data using databases and analytics tools.
• Strong working knowledge of SQL in a relational database environment.
• Solid experience using Python for data analysis and automation.
• Experience with machine learning and predictive analytics is advantageous.
• Background in
  financial services
  preferred, ideally with exposure to
  insurance
  or
  investment management
  sectors.
• Experience working within an
  audit
  or
  risk management
  environment is highly desirable.
• Exceptional attention to detail and logical problem-solving abilities.
• A collaborative team player with the ability to build and maintain professional respect within the team and across departments.

• Assist in collecting, cleaning, and organizing data from various sources.
• Perform data analysis under the guidance of senior team members.
• Identify trends, patterns, and insights within datasets.
• Contribute to the development of reports and data visualizations.
• Learn and apply data analysis tools and techniques (e.g., SQL, Python, R, Tableau).
• Support the creation of dashboards and performance metrics.
• Participate in team meetings and contribute to project discussions.
• Conduct research on data-related topics and best practices.
• Maintain data integrity and accuracy.
• Develop a strong understanding of business requirements and how data can address them.

• Recent graduate with a Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong understanding of statistical concepts and data analysis principles.
• Familiarity with programming languages like Python or R is a plus.
• Basic knowledge of SQL and database concepts.
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills.
• Ability to work independently and collaboratively in a remote environment.
• Eagerness to learn and a passion for data.

• Gain foundational knowledge and practical skills in data analysis techniques.
• Work with diverse datasets to identify trends, patterns, and insights.
• Learn to use various data analytics tools and software (e.g., SQL, Python, R, Tableau).
• Assist in the development of reports and dashboards to communicate findings effectively.
• Participate in team projects, contributing to data-driven decision-making processes.
• Receive regular feedback and mentorship from senior data analysts and scientists.
• Explore different areas of data analytics, including business intelligence, predictive modeling, and data visualization.
• Understand data governance principles and best practices.
• Develop strong problem-solving and analytical thinking skills.
• Engage in continuous learning and professional development through assigned modules and workshops.

• Recent graduate with a Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline.
• Strong analytical and problem-solving abilities with a keen eye for detail.
• Proficiency in basic statistical concepts.
• Familiarity with programming concepts (e.g., Python or R) is a plus.
• Excellent communication skills, both written and verbal.
• Proactive, eager to learn, and a strong team player.
• Ability to work independently and manage time effectively in a remote environment.
• Demonstrated interest in data analysis and technology.

• Assisting in the collection, cleaning, and processing of data.
• Performing basic data analysis to identify trends and patterns.
• Supporting the creation of reports and dashboards.
• Learning and applying data analysis tools and techniques.
• Collaborating with team members on data-related projects.
• Contributing to data quality assurance efforts.
• Developing an understanding of business requirements for data analysis.

• Recent graduate with a Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong analytical and problem-solving skills.
• Basic understanding of statistical concepts.
• Proficiency in Microsoft Excel.
• Eagerness to learn data analysis tools (e.g., SQL, Python, R, Tableau) and methodologies.
• Excellent communication and interpersonal skills.
• Ability to work independently and manage time effectively in a remote environment.