Associate Data Analytics Engineer

Job Purpose

To improve the quality and accuracy of the information, enabling businesses to make more responsible business decisions. They also work with leaders across the organization to help support business decisions.

Key Result Responsibilities

1. Data Pipeline Development:Assist in designing, developing, and maintaining data pipelines for efficient data extraction, transformation, and loading (ETL) processes.
2. Implement data integration solutions to connect and consolidate data from diverse sources.
3. Database Management:: Support the management of databases and data warehouses, ensuring optimal performance, reliability, and scalability.
4. Collaborate with database administrators to implement best practices for data storage and retrieval.
5. Data Quality Assurance: : Collaborate with data analysts and data scientists to understand data requirements and ensure the quality and accuracy of datasets.
6. Implement data validation and cleansing processes to identify and rectify anomalies.
7. Coding and Scripting: : Utilize programming languages (e.g., Python, Java, SQL) to write and maintain efficient and scalable code for data processing tasks.
8. Collaborate with software engineers to integrate data engineering solutions into larger software systems.
9. Documentation: :Document data engineering processes, workflows, and data architectures to ensure knowledge transfer and maintain a comprehensive reference for future development.
10. Collaboration:Work closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and provide technical support.
11. Continuous Learning: Stay abreast of industry trends, emerging technologies, and best practices in data engineering to contribute to the improvement of data processes

Key Result Responsibilities-Continued

Qualifications (Academic, training, languages)

Work Experience

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Strong programming skills with proficiency in languages such as Python, Java, or SQL.
• Familiarity with data processing frameworks and tools (e.g., Apache Spark, Hadoop).
• Knowledge of database management systems (e.g., MySQL, PostgreSQL, MongoDB).
• Understanding of data modeling concepts and database design principles.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• Ability to work in a fast-paced and dynamic environment.