Enterprise Data Pipeline Developer
7 days ago
SID Global Solutions APAC is seeking an experienced Enterprise Data Pipeline Developer to join our team. The ideal candidate will have 3-5 years of experience in developing and managing data pipelines, optimizing data infrastructure, and collaborating with data scientists and analysts to support data-driven decision-making.
This role will be focused on building and maintaining enterprise-level data pipelines that ensure accurate and efficient data flow across various systems.
Key Responsibilities:
- Design and Develop Data Pipelines: Build, maintain, and optimize scalable data pipelines to ingest, transform, and load data across various platforms (cloud and on-premise).
- ETL Process Management: Lead the development and optimization of ETL (Extract, Transform, Load) processes to ensure seamless data flow, integrity, and consistency across internal and external systems.
- Database Management: Manage and optimize relational and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra) for performance, reliability, and scalability.
- Cloud Data Infrastructure: Work with cloud platforms such as AWS, Google Cloud Platform (GCP), or Azure to deploy and scale data solutions.
- Data Warehousing: Build and maintain data warehousing solutions, ensuring the efficient and reliable storage of large datasets.
- Data Quality Assurance: Ensure the accuracy, consistency, and availability of data by implementing data quality and validation checks across data pipelines.
- Automation and Monitoring: Automate routine tasks and implement monitoring to ensure data systems and pipelines run efficiently with minimal downtime.
Required Skills and Qualifications:
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- 3-5 years of experience in data engineering or a similar role, ideally in a fast-paced, data-driven environment.
- Proficiency in SQL and experience working with relational databases.
- Strong programming skills in Python, Java, or Scala for building data pipelines.
- Experience with ETL tools for automating data workflows.
- Hands-on experience with cloud data services such as AWS (Redshift, S3, Lambda), Google Cloud Platform (BigQuery, Cloud Storage), or Microsoft Azure.
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