Data Engineer
Data Engineer
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Job Description
Job Specifics:
- Location: Kigali Rwanda
- Job Type: Fulltime Permanent
- Work Type: Remote Open to candidates that reside in Kigali Rwanda
Overview:
As a Data Engineer you will play a critical role in designing developing and maintaining scalable data pipelines and infrastructure to enable datadriven applications and analytics solutions. This position requires proficiency in developing robust data architectures optimizing data workflows and contributing to the strategic advancement of data initiatives. Collaboration with crossfunctional teams is integral to this role.
Key Responsibilities:
- Data Pipeline Development: Design implement and maintain scalable data pipelines using tools like Databricks Python and PySpark.
- Data Architecture: Build scalable and efficient data solutions leveraging modern data architectures.
- Data Modelling: Optimize data models and schemas for structured and unstructured data storage and analysis.
- ETL Development: Develop automate and optimize ETL workflows.
- Big Data Technologies: Utilize technologies such as Spark Kafka and Flink for distributed data processing.
- Cloud Platforms: Deploy and manage data solutions on platforms like AWS Azure or Google Cloud.
- Data Governance: Ensure data quality governance and security compliance.
- Performance Monitoring: Monitor troubleshoot and optimize data pipelines.
- DevOps Practices: Develop and maintain CI/CD pipelines and manage code in version control systems.
- Innovation: Stay updated on emerging technologies and implement best practices in data engineering cloud solutions and DevOps.
- Technology Evaluation: Assess and recommend tools frameworks and platforms for data solutions.
- Optimization: Optimize software performance through thoughtful design and tuning.
Qualifications and Skills:
- Programming: Proficiency in Python or Java and SQL.
- Data Modelling: Experience with creating and optimizing data models.
- Big Data Tools: Familiarity with tools like Databricks Spark Kafka and Flink.
- Modern Architectures: Knowledge of lakehouse architectures.
- Data Integration: Experience with data ingestion from diverse sources (e.g. REST APIs SQL MongoDB SFTP).
- CI/CD and Version Control: Expertise in building CI/CD pipelines and working with Git and containerization tools like Docker.
- ETL Tools: Handson experience with tools such as Apache Airflow Informatica DBT or Talend.
- Governance: Deep understanding of data governance best practices.
- RealTime Data: Familiarity with realtime streaming technologies like Apache Spark Streaming and Kafka.
- Cloud Tools: Proficiency with cloud data tools including AWS Azure or GCP (e.g. S3 EMR Redshift Glue Azure Data Factory BigQuery Dataflow).
This role provides an opportunity to work on cuttingedge data engineering projects leveraging advanced technologies to drive impactful solutions.
Employment Type
Full Time
