Data Analytics Engineer
Henkel AG & Co. KGaA5 months ago
Cairo, EgyptMid Level
Responsibilities
- Design, build, and maintain analytical data models, cubes, and semantic models for reporting and advanced analytics.
- Develop scalable data pipelines on Databricks using Python and Spark.
- Manage end-to-end data assets from ingestion through curated datasets for BI consumption.
- Ensure data quality, consistency, and performance across analytics solutions.
- Collaborate with business stakeholders, analysts, and data teams to translate requirements into scalable solutions.
- Contribute to modern analytics architecture, best practices, and reusable frameworks.
- Use AI-powered tools such as Copilot, Genie, and LLM-based solutions to improve development efficiency and explore new use cases.
- Explore technologies and drive improvements across the data landscape.
Requirements
- Experience designing analytical data models and cubes, including Azure Analysis Services or semantic models.
- Experience developing scalable data pipelines with Databricks, Python, and Spark.
- Ability to build and manage data assets from ingestion through BI-ready curated datasets.
- Ability to address data quality, consistency, and performance optimization.
- Ability to collaborate with stakeholders, analysts, and data teams on scalable analytics solutions.
Tech Stack
Categories
Data Engineering
About Henkel AG & Co. KGaA
Henkel AG & Co. KGaA manufactures and sells products across two divisions: Adhesive Technologies for industrial customers and Consumer Brands for households and salons. It supplies adhesives, sealants, and surface treatments to sectors such as automotive, electronics, and packaging, and markets laundry, home care, and hair care lines under brands including Persil, Schwarzkopf, and Loctite. Founded in 1876 and headquartered in Düsseldorf, Germany, it is publicly traded in Frankfurt.