Senior Data Engineer at Digital 4 Africa

1 month ago


Nairobi, Kenya Digital 4 Africa Full time

We are a team of skilled UX designers, software engineers, data scientists and content writers with years of experience in digital marketing.
Summary


This Senior Data Engineer position requires a comprehensive skill set in data science, machine learning, and data engineering. Here's a breakdown of the key qualifications and responsibilities:
Skills:

Python Expertise: Strong programming in Python for data science and machine learning.
Data Science Libraries: Experience with libraries such as Matplotlib, Pandas, NumPy, and Scikit-learn.
ETL: Experience with Extract Transform Load (ETL) processes
Data Analysis Tools: Have Data Analytics skills. Expert in Jupyter Notebooks, Google Colabs, and Kaggle.
Data Visualization: Expertise in Microsoft Power BI for creating interactive dashboards and reports.
Data Modelling: Proficient in Excel formulas and functions (e.g., VLOOKUP, INDEX-MATCH, pivot tables, and macros).
SQL Knowledge: Knowledge of SQL for querying and managing data from various sources.
Cloud Platforms: Experience with cloud platforms such as Azure or AWS is a plus.
Data Scraping and API: Expertise in data scraping and working with API technologies.

Responsibilities:

Team Supervision: Supervise a junior data engineer.
Data Pipeline Development: Assist in the design, development, and maintenance of data pipelines and workflows.
Data Collection and Cleaning: Collect, clean, and transform data from various sources, including APIs, web scraping, or surveys.
Data Analysis: Analyze and interpret data using descriptive and inferential statistics, machine learning, or other methods.
Data Product Delivery: Create and deliver data products, such as dashboards, reports, and visualizations, using Microsoft Power BI, Excel, and Python.
Decision Support: Provide data insights and recommendations to support decision-making and problem-solving for various projects and clients.
Collaboration: Collaborate with other data engineers, analysts, and stakeholders to ensure data quality and consistency.


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