Data Pipeline Engineer

14 hours ago

Bonifacio Global Metro Manila, Philippines UPTC Full time $60,000 - $120,000 per year
Qualifications
  • Bachelor's degree in Engineering, IT, Computer Science, or related technical field.
  • Minimum 5 years of experience in a Data Engineering role.
  • Hands-on experience in data modeling and database design.
  • Proficient with big data tools such as Hadoop, Spark, Kafka.
  • Strong experience with relational SQL and NoSQL databases (e.g., PostgreSQL, Cassandra).
  • Experience with data pipeline and workflow management tools such as Airflow, Luigi, Azkaban.
  • Practical knowledge of AWS cloud services including EC2, EMR, RDS, Redshift.
  • Experience with stream-processing systems such as Storm or Spark Streaming.
  • Skilled in object-oriented and functional programming using Python, Java, C++, Scala, or similar languages.
  • Advanced SQL expertise with experience in writing complex queries and managing relational databases.
  • Proven ability to build, optimize, and maintain large-scale data pipelines, architectures, and datasets.
  • Strong analytic skills, particularly in working with unstructured datasets.
  • Experience performing root cause analysis to identify data issues and opportunities for process improvement.
  • Knowledge of message queuing, stream processing, and scalable "big data" stores.
  • Strong project management and organizational skills.
  • Experience collaborating with cross-functional teams in dynamic environments.

Job Description
  • Design, build, and maintain highly scalable data management systems and pipelines.
  • Develop and optimize data architectures and datasets for efficient storage and retrieval.
  • Implement and manage ETL processes for accurate, timely integration across multiple systems.
  • Perform data modeling to design databases that meet business and analytical requirements.
  • Build and maintain data workflows using tools such as Airflow, Luigi, or Azkaban.
  • Process and manage large datasets using big data technologies (Hadoop, Spark, Kafka).
  • Handle real-time data flows with stream-processing systems like Storm or Spark Streaming.
  • Utilize relational and NoSQL databases for structured and unstructured data management.
  • Leverage AWS cloud services (EC2, EMR, RDS, Redshift) for scalable and reliable data infrastructure.
  • Write and maintain complex SQL queries and scripts for extraction, transformation, and analysis.
  • Use Python, Java, C++, Scala, or similar languages for developing data engineering solutions.
  • Conduct root cause analysis on data and processes to identify issues and implement improvements.
  • Maintain metadata management, data transformation, and dependency tracking processes.
  • Collaborate with data analysts, data scientists, and business teams to deliver reliable datasets.
  • Ensure data accuracy, consistency, and security across multiple environments.
  • Implement monitoring systems for pipelines and troubleshoot data flow issues.
  • Document data architecture, processes, and workflow dependencies.
  • Manage multiple data engineering projects while ensuring timelines, quality, and efficiency.
  • Continuously evaluate new tools and technologies to improve data scalability, efficiency, and performance.

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