Data Engineer

4 weeks ago


Abu Dhabi, United Arab Emirates Marc Ellis Full time
Job Type: 12 Months Extendable

Responsibilities:•Experience with handling large volumes of unstructured data (TBs ideally), looking for proficiency beyond structured databases like MySQL.•Experience with various tools such as Kibana, Power BI, and optionally, Neo4j for graph visualization.•Expert level of proficiency in Python programming.•Must have managed large scale of data, both in terms of storage (GBs) and records/files (multi-million) as the role involves handling TBs of data.•Oversee and manage architecture on Azure platform for efficient data operations.•Experience in working with audio, video, or image data.•Development Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics.•Experience in utilizing Hugging Face models for various tasks.•Work closely with data scientists, ML engineers, and stakeholders to ensure that data is accessible, consistent, and reliable for ongoing projects.•Develop and maintain APIs for data access and manipulation and integrate with external data services as needed.•Manage and optimize data storage solutions, including relational databases, Search Engines like Elasticsearch and NoSQL databases, to support the requirements of machine learning models.•Implement processes to monitor data quality and ensure production data is always accurate and available for key stakeholders.•Collaborate with ML engineers to assist in data-related technical issues and provide architectural guidance and solutions.•Ensure compliance with data security and privacy policies.•Maintain clear and up-to-date documentation including data dictionaries, metadata, and architectural diagrams.Skills and attributes for success•Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or equivalent work experience.•3+ years of experience in a Data Engineering role.•Knowledge / skills in various data science techniques and NLP.•Optional experience in Pyspark and big data handling.•Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar.•Strong understanding of data warehousing concepts, ETL processes, and data modeling.•Knowledge in DevOps, CI/CD methods, and containerization technologies like Docker or Kubernetes.•Experience with real-time data processing.

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