Assistant Manager - Data Engineering at Kenya Revenue Authority (KRA)

Department       Corporate Support Services (CSSD)

Division Technology, Innovation and Artificial Intelligence

Section / Unit     Data Analytics & AI Solutions

Job Purpose

• The Data Integration Engineer is responsible for:
• Designing/optimization of KRA’s data warehousing and big data platforms.
• Leveraging on appropriate technologies to deliver robust processes for real-time/near real-time data ingestion, job automation and model deployments.
• Creating reproducible lean engineering processes for better memory and space management of data management solutions.
• Proactively building and implementing services, including end to end monitoring of data pipelines and platforms, scripting and automation of data lifecycle and quality processes.
• Problem resolution for recurrent incidents escalated by support teams around data analytics solutions.
• Co-ordination and supervision of assigned development teams.
• Development or enhancements to existing data services in line with procedures and standards.

Key Responsibilities

• Identifying different sources of data and building a roadmap for real-time / near real-time data collection.
• Responsible for Data Integration into the Enterprise Data Warehouse and Big Data Platforms in projects, and supporting business teams in data quality automation.
• Responsible for planning, research, design and implementation of new data analytics platforms and technologies to address the organization’s analytics demands including big data platforms.
• Responsible for automating big data lifecycle management, big data storage systems, data security and data governance.
• Responsible for design and implementation of processes to ensure data reliability, efficiency, quality, and continuous improvement.
• Responsible for eliminating tool redundancy and ensuring timely data availability.
• Responsible of performing analytics infrastructure sizing based on requirements and design in projects.
• Responsible of creating data pipelines using both proprietary and emerging technologies (like Apache Nifi and Kafka among others).
• Identification of the correct analytics technology stacks to use as per project requirements.
• Technical responsibility for working with business in identification, development, piloting and scaling of ML and AI use cases.
• Working closely with BI support and application support teams to make sure that all the big data applications and pipelines are highly available and performing as expected.
• Reviewing design and architecture to guarantee service availability, performance and resilience.
• Reviewing application development tasks allocated to supervised staff to ensure that they are accomplished within the set requirements and that they meet highest standards of quality.
• Ensuring that solutions built comply with quality assurance (including fixing of functional and non-functional issues) and release guidelines; and have the requisite documentation.
• Planning for solution demos for delivered solutions/enhancements to get stakeholder feedback and for adoption.
• Reviewing analytics domain coding standards and recommends/implements improvements.

Academic qualifications

• Bachelor’s degree in Computer Science, Information Systems, Information Technology, Analytics or other related fields from a recognized university.

Professional Qualifications/Certifications

• Data Warehousing Solutions design, setup and optimization.
• Big Data Platforms design, setup and optimization.
• Structured and Unstructured Database Systems.
• ETL / ELT Jobs design, optimization and tooling.
• Machine Learning and AI an added advantage.
• Data Architecture and Design an added advantage. 

Work experience required

• Four (4) years of hands-on experience of which one (1) should be at Supervisory level working with Java and experience in Python, R, SQL and Scala in the analytics field within a busy environment processing large and high velocity data sets.
• Proven experience in design, development and implementation of big data processing architectures and data ingestion techniques.
• Demonstrated experience in big data querying techniques and tools.
• Working experience in solutions development and delivery using agile frameworks will be an added advantage.

Functional and Technical Skills

• Hands-on experience in implementing, managing, monitoring and administering overall Hadoop infrastructures as well as development and monitoring of Hadoop jobs.
• Hands-on experience in structured and unstructured databases administration and development.
• Hands-on experience supporting installation and code deployments into Hadoop clusters
• Experience in sizing & capacity planning of data platforms as per data requirements.
• Hands-on experience monitoring and reporting on Hadoop resource utilization and troubleshooting.
• Hands-on experience in doing data backup and recovery tasks.
• Experience in data lifecycle management (including data retention and purging strategies)
• Experience in ETL, big data jobs, data streams processing and database performance optimization.
• Hands-on experience in installation and performance maintenance of Apache Nifi, Apache Kafka, Airflow and ML flow.
• Experience with ML/AI model deployments will be an added advantage
• DevOps and infrastructure automation experience (containerization technologies, Ansible, etc.) will be an added advantage.
• Working knowledge of Linux/Unix and Windows operating system platforms.

Behaviours and Competencies

• Demonstrated analytical, technical, and problem-solving skills, with high-levels of creativity and a practical approach that is self and principle-driven.
• Ability to balance the long-term and short-term implications of individual decisions and effective at driving short-term actions that are consistent with long-term goals.
• Ability to interact confidently with users to establish real problems and explain the solutions while prioritizing competing work commitments and delivering on time.
• Excellent written and verbal communications skills, able to distil complex technical concepts into simple terms, with strong persuasion skills to gain support for and establish principles, standards, and change.
• Excellent relationship building, teamwork, and collaboration skills that enables the provision of effective support and guidance across programs as well as negotiation.
• Vendor and technology neutral –driven primarily by long-term business outcomes rather than personal preferences.
• Be resilient, focused, results oriented and a team player.