Data Engineer
  • Create and manage ETL data pipelines using Python, Spark, and Airflow.
  • Create and manage real-time pipelines using Kafka.
  • Improve and maintain the data lake setup (S3, EMR, Presto).
  • Integrate data from 3rd party APIs (e.g. Hubspot, Facebook).
  • Ensure data quality through automated testing.
  • Develop and maintain company metrics and dashboards.
  • Collaborate with analysts, engineers, and business users to design solutions.
  • Research innovative technologies and make continuous improvements.

You may be a good fit if
  • 3+ year as a data engineer developing and maintaining ETL pipelines.
  • Experience in building data lake/warehouse solutions consisting of structured and unstructured data.
  • Hands-on experience with big data technologies (e.g. Spark, Hive)
  • Experience in writing and optimizing SQL queries.
  • Good knowledge of Python.
  • Hands-on experience with BI tools (e.g. Looker, Redash).
  • Bachelor's degree in a technical field or equivalent work experience.
  • Have experience managing and designing data pipelines, debugging data issues.
  • Are familiar with real-time and/or large scale data.
  • You have built data products that have scaled on AWS or another cloud.
  • You thrive on nimble, lean, fast-paced startups, like autonomy, and have proven you can push towards a goal by yourself.
  • Coachable. Able to own mistakes, reflect, and take feedback with maturity and a willingness to improve.
  • You communicate with clarity and precision and you are able to effectively present results

Interested? Apply this vacancy on:

Work Opportunity at Xendit Indonesia in May 2022 - Loker Startup

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