Senior Data Engineer
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Key skills for this role
About the Role
Presight is hiring a Senior Data Engineer to build and maintain data infrastructure supporting big data analytics and AI. The role involves designing scalable data pipelines, managing data storage, and collaborating with data scientists.
Key Skills for This Role
Responsibilities
- Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics
- 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 for both structured and unstructured data
- 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
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or equivalent work experience
- 7+ years of experience in a Data Engineering role
- Programming languages like Python and SQL and managing huge scale data potentially Terabyte to Petabyte
- Hands on experience with big data technologies like Spark (Using PySpark / Scala) and Flink
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar
- Strong understanding of data warehousing or Lake house concepts, ETL processes, and data modeling
- Experience with API development and integration with data services
- Experience with cloud platforms like Azure
- Knowledge in DevOps, CI/CD methods, and containerization technologies like Docker or Kubernetes
- Experience with real time / streaming data processing
Full Job Posting
Overview
- Presight is an ADX listed public company with Abu Dhabi based G42 as its majority shareholder and is the region’s leading big data analytics company powered by GenAI.
- As a Senior Data Engineer, you will be responsible for building and maintaining the infrastructure that supports data collection, processing, and storage.
Responsibilities
- Data Pipeline Architecture and Development: Design, construct, install, test, and maintain highly scalable data pipelines with a focus on machine learning models and analytics.
- Data Integration: Work closely with data scientists, ML engineers, and stakeholders to ensure that data is accessible, consistent, and reliable for ongoing projects.
- API and Data Services: Develop and maintain APIs for data access and manipulation, and integrate with external data services as needed.
- Data Storage: Manage and optimize data storage solutions for both structured and unstructured data.
- Data Quality and Governance: Implement processes to monitor data quality and ensure production data is always accurate and available for key stakeholders.
- Collaboration and Support: Collaborate with ML engineers to assist in data related technical issues and provide architectural guidance and solutions.
- Security and Compliance: Ensure compliance with data security and privacy policies.
- Documentation: Maintain clear and up to date documentation including data dictionaries, metadata, and architectural diagrams.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; or equivalent work experience.
- 7+ years of experience in a Data Engineering role.
- Programming languages like Python and SQL and managing huge scale data potentially Terabyte to Petabyte.
- Hands on experience with big data technologies like Spark (Using PySpark / Scala) and Flink.
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar.
- Strong understanding of data warehousing or Lake house concepts, ETL processes, and data modeling.
- Experience with API development and integration with data services.
- Experience with cloud platforms like Azure.
- Knowledge in DevOps, CI/CD methods, and containerization technologies like Docker or Kubernetes.
- Experience with real time / streaming data processing.
Technical stack
- Programming Languages: Python, SQL
- Query Engine: Trino
- Big Data Technologies: Spark, Flink
- Unstructured Data: Text, Image, Audio & Video
- Databases: Clickhouse, MySQL, PostgreSQL, MongoDB, Cassandra, HBase, Redis
- Cloud Platforms: Azure
- API Development: RESTful APIs, GraphQL, OpenAPI
- Data Services: Kafka, RabbitMQ
- Containers: Docker, Kubernetes
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