Senior Data Engineer - Singapore

at  BBGC

Job Description: Senior Data Engineer
Position Overview: We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. The Senior Data Engineer will be responsible for designing, implementing, and maintaining scalable data pipelines and infrastructure to support our organization’s data needs. The ideal candidate will have a strong background in data engineering, expertise in various data technologies, and a passion for building robust and efficient data solutions.

Key Responsibilities:

• Design, develop, and maintain data pipelines and ETL processes to ingest, process, and transform large volumes of structured and unstructured data from multiple sources.
• Collaborate with cross-functional teams including data scientists, analysts, and software engineers to understand data requirements and implement solutions that meet business needs.
• Optimize and tune data pipelines and workflows for performance, scalability, and reliability.
• Implement data governance processes and ensure data quality and integrity throughout the data lifecycle.
• Design and maintain data warehouse and data lake architectures to store and organize data for analytics and reporting purposes.
• Research and evaluate new technologies and tools to enhance our data infrastructure and capabilities.
• Provide technical leadership and mentorship to junior members of the data engineering team.
• Collaborate with infrastructure and DevOps teams to deploy and manage data solutions in cloud-based environments.
• Develop and maintain documentation for data pipelines, systems, and processes.
• Stay current with industry trends and best practices in data engineering and apply them to improve our data ecosystem.

Qualifications:

• Bachelor’s degree or higher in Computer Science, Engineering, or a related field.
• X+ years of experience in data engineering, with a proven track record of designing and implementing complex data solutions.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with data processing frameworks like Apache Spark or Apache Flink.
• Strong experience with distributed data storage and processing technologies such as Hadoop, Apache Kafka, Apache HBase, or similar.
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, and familiarity with related services such as AWS EMR, S3, Glue, or Azure Data Factory.
• Experience with SQL and relational databases (e.g., PostgreSQL, MySQL) as well as NoSQL databases (e.g., MongoDB, Cassandra).
• Solid understanding of data modeling concepts and proficiency in designing efficient data schemas.
• Excellent problem-solving skills and the ability to troubleshoot complex data issues.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.
• Experience with Agile development methodologies and tools like JIRA is a plus.

This job description outlines the primary responsibilities and qualifications for the Senior Data Engineer role. Candidates should possess a combination of technical expertise, analytical skills, and teamwork abilities to excel in this position

• Design, develop, and maintain data pipelines and ETL processes to ingest, process, and transform large volumes of structured and unstructured data from multiple sources.
• Collaborate with cross-functional teams including data scientists, analysts, and software engineers to understand data requirements and implement solutions that meet business needs.
• Optimize and tune data pipelines and workflows for performance, scalability, and reliability.
• Implement data governance processes and ensure data quality and integrity throughout the data lifecycle.
• Design and maintain data warehouse and data lake architectures to store and organize data for analytics and reporting purposes.
• Research and evaluate new technologies and tools to enhance our data infrastructure and capabilities.
• Provide technical leadership and mentorship to junior members of the data engineering team.
• Collaborate with infrastructure and DevOps teams to deploy and manage data solutions in cloud-based environments.
• Develop and maintain documentation for data pipelines, systems, and processes.
• Stay current with industry trends and best practices in data engineering and apply them to improve our data ecosystem