Senior Data Infrastructure Specialist

2 days ago


Pasay, National Capital Region, Philippines beBeeDataEngineer Full time ₱500,000 - ₱1,000,000

At the forefront of financial data innovation, we are looking for a skilled Data Engineer to join our global team.

This is a unique opportunity to shape the future of our data infrastructure and processes, driving impactful projects from the ground up.

Job Description

As a key member of our engineering function, you will play a crucial role in developing and maintaining data pipelines, data warehouses, and cloud-based systems.

  • Create performant batch and streaming data pipelines capable of handling large volumes of data in both real-time market data and batch formats (Apache Airflow, Apache Kafka, Apache Flink).
  • Utilize tools like Snowflake to construct reliable and scalable data warehousing solutions.
  • Employ Amazon Web Services (AWS) or Google Cloud Platform (GCP) to build robust and scalable cloud-based systems.
  • Improve Continuous Integration/Continuous Deployment processes using tools like Jenkins and GitLab to automate development, testing, and deployment.
Required Skills and Qualifications

To be successful in this role, you will need:

  • 5+ years of work experience in data engineering or similar
  • Bachelor's degree in computer science, engineering, mathematics, or a related technical field.
  • Experience hiring, mentoring and leading junior engineers
  • Proficiency in Python with at least one data manipulation framework (e.g. Pandas, Dask, Pyspark) and SQL; knowledge of other languages like Java, C#, or C++ is advantageous.
  • Experience with REST APIs and building scalable API data platform (e.g. FastAPI)
  • Experience with AWS, Snowflake, Kubernetes, and Airflow.
  • Experience with Prometheus, Grafana, CloudWatch for monitoring and alerting
  • Comfortable with Linux and command line operations.
  • Understanding of ETL processes and event streaming technologies (such as Kafka, Flink, etc.).

Please note that prior experience working with financial market data is beneficial but not required.



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