Data Engineering Senior Manager

2 days ago

Pasig, National Capital Region, Philippines Jollibee Group Full time

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The Senior Data Engineer is a pivotal role responsible for designing, developing, and leading the implementation of scalable data pipelines and infrastructure. You will collaborate closely with cross-functional teams to understand and shape business requirements into advanced data engineering solutions. Additionally, you will optimize data platforms like Snowflake and Databricks, ensure data security, governance, and compliance, and mentor junior engineers. Your extensive experience in programming, big data technologies, and cloud platforms will be crucial in driving innovation, technical leadership, and continuous improvement within the team.

JOB EXPERIENCES and SKILLS REQUIRED

  • 5-8 years of experience in data engineering with a strong track record of leading complex projects and teams.
  • Advanced proficiency in programming languages such as Python, Java, or Scala, with demonstrated expertise in software engineering best practices.
  • Extensive experience with data warehouse technologies, particularly Snowflake and Databricks, including optimization and strategic roadmap development.
  • Deep expertise in big data technologies such as Hadoop, Spark, and Hive, with practical experience in managing and optimizing large-scale data environments.
  • Experience with real-time data streaming and processing using tools like Apache Kafka, with a focus on event-driven architectures.
  • Advanced understanding of data modeling, ETL processes, and data pipeline architecture, with a track record of applying best practices.
  • Proven problem-solving skills, with the ability to troubleshoot and resolve complex data issues and provide strategic solutions.
  • Excellent communication and leadership skills, with experience mentoring junior engineers and leading cross-functional teams.
  • Proven ability to work independently while also leading collaborative efforts within a team.
  • Experience in driving the adoption of new tools and technologies and integrating them into existing data engineering practices.
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