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Develop and manage ETL/ELT workflows to ensure efficient data processing and availability for AI/ML applications.
Optimize data storage, retrieval, and processing performance across large datasets.
Prepare, clean, and transform datasets required for training, validating, and testing machine learning models.
Collaborate with data scientists and ML engineers to ensure data readiness for model development and experimentation.
Support feature engineering processes and maintain feature stores where applicable.
Build and manage data infrastructure that supports AI/ML workloads, including batch and real\-time processing systems.
Implement scalable data architectures using cloud platforms or distributed systems.
Ensure high data availability, integrity, and reliability across data environments.
Implement data validation, monitoring, and quality control processes.
Ensure data governance policies, compliance standards, and security best practices are followed.
Manage metadata, data lineage, and documentation for AI/ML datasets.
Work closely with data scientists, analysts, and software engineers to operationalize machine learning models.
Support deployment of ML models into production environments through robust data infrastructure.
Continuously evaluate new tools, technologies, and frameworks to improve data engineering and AI capabilities.
Bachelorâs degree in Computer Science, Data Engineering, Software Engineering, Artificial Intelligence, or a related field.
3+ years of experience in data engineering, data platforms, or related technical roles.
Experience working with machine learning pipelines or AI\-driven data environments.
Proven experience building scalable data pipelines and managing large datasets.
Strong proficiency in Python, SQL, or Scala.
Experience with data pipeline tools such as Apache Airflow, Kafka, or similar frameworks.
Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and cloud\-based data services.
Experience with data warehousing solutions such as Snowflake, BigQuery, or Redshift.
Understanding of machine learning workflows and data preparation techniques.
Strong analytical and problem\-solving skills.
Ability to work collaboratively in cross\-functional teams.
Good documentation and communication skills.
Strong attention to data quality, security, and governance practices.
Qore provides the rare opportunity to make history in the financial space for Africa by Africans, while working with the smartest, brightest & coolest minds in Africa. Our people & culture team continuously thinks of innovative ways to improve employee experience and some of the other benefits of working with Qore includes:
