Job Description

What we are looking for

Were looking for a candidate with a foundational understanding of data engineering concepts and handson experience with relevant technologies. This role provides the opportunity to grow into a senior data engineering position contributing to innovative cloudbased projects.

What does the job involve

• Data Pipeline Development: Assist in implementing and maintaining scalable data pipelines for ingesting processing and transforming large volumes of data from various sources using tools such as Databricks Python and PySpark.
• Data Modeling: Assist in designing data models and schemas for efficient storage retrieval and analysis of structured and unstructured data.
• ETL Processes : Develop and automate ETL workflows to extract data from diverse sources transform it into usable formats and load it into data warehouses data lakes or lakehouses.
• Big Data Technologies: Utilize big data technologies such as Spark Kafka and Flink for distributed data processing and analytics.
• Cloud Platforms: Collaborate with the team to deploy data solutions on cloud platforms such as AWS Azure or Google Cloud Platform (GCP) leveraging cloudnative services for data storage processing and analytics.
• Data Quality and Governance: Implement data quality checks validation processes and data governance policies to ensure accuracy consistency and compliance with regulations.
• Monitoring and Troubleshooting: Monitor data pipelines and assist in troubleshooting and resolving datarelated issues.
• DevOps: Commit code to version control.
• Collaboration: Collaborate with crossfunctional teams including data scientists analysts and software engineers to understand requirements and deliver datadriven solutions.
• Documentation: Create and maintain technical documentation including data architecture diagrams ETL workflows and system documentation to facilitate understanding and maintainability of data solutions.
• Best Practices : Continuously learn and apply best practices in data engineering and cloud computing.

Qualifications

• Programming Languages: Experience with Python Java Scala or SQL for data manipulation and scripting.
• Big Data Technologies: Experience with Databricks Spark Kafka and Flink.
• Version Control : Experience with systems like Git.
• Cloud Platforms: Familiarity with AWS Azure or GCP services.
• SQL: Proficiency in SQL for database management and querying.
• Apache Spark: Knowledge of Apache Spark for distributed data processing.
• Modern Data Architectures : Exposure to modern data architectures such as lakehouse.
• ETL Tools: Knowledge of ETL tools and technologies such as Apache Airflow Informatica or Talend.
• Cl oud Data Tools : Familiarity with cloud data services like AWS S3 EMR Redshift Glue Azure Data Factory Databricks BigQuery Dataflow and Dataproc.

Benefits

Competitive Salary

Location

Remote Egypt Kenya South Africa Nigeria

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