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Xendit

Gaji Kompetitif

Jakarta

Staff Data Engineer

Minimum Qualifications

  • 5+ years of relevant experience as a data engineer.
  • 2+ years of relevant experience as senior/staff/principal data engineer.
  • Excellent knowledge of Python, SQL, and Apache Spark.
  • Excellent knowledge of at least 1 real-time data processing framework such as Spark Streaming, Flink, or Kafka.
  • Demonstrated ability to design and build high-volume batch and streaming pipelines.
  • Demonstrated ability to design and build scalable data infrastructure.
  • Working experience with designing and implementing data quality checks and alerting systems.
  • Working experience in optimizing SQL queries in OLAP cluster (e.g. data partitioning, bucketing, z-ordering, indexing).
  • You are coachable. Able to own mistakes, reflect, and take feedback with maturity and a willingness to improve.
  • Strong written and verbal communication skills.
  • Bachelor’s degree in a technical field or equivalent work experience.

Preferred Qualifications

  • Working experience in developing a Python library used by internal teams. Including best practices for development and deployment.
  • You have a good knowledge of Terraform, CloudFormation, or other IaaC tools.
  • You have built data products that have scaled on AWS or another cloud.
  • You have experience with modern data tools such as Airflow, dbt, Kafka, Trino, Databricks, Looker, or similar.
  • You have experience with different databases or SQL engines and understand their trade-offs (e.g. Trino, Druid, PostgreSQL, MongoDB, etc.).
  • You have worked with sensitive data and ensured secure access through a data governance tool.
  • You have worked on building a Data platform that enables stakeholders to self-serve.

Responsibilities

  • Improve data pipeline logic to ensure reliability, scalability, and cost efficiency (Python, Spark, Airflow).
  • Ensure fast and reliable execution of analytical queries by building robust OLAP cluster (Trino, Terraform, Databricks SQL warehouse).
  • Design and implement a data governance policy to minimize security risks (Unity Catalog, Apache Ranger).
  • Own design and development of Data engineering’s internal library (Python, Spark, dbt).
  • Enable internal teams to build real-time applications on top of the Data lakehouse. (Spark streaming, Kafka)
  • Automate common data requests and unlock self-service (Retool, Flask).
  • Ensure high data quality through automated tests and data contracts (dbt, Great expectations).
  • Improve deployment process for various applications (Buddy).
  • Collaborate with other data engineers, analysts, and business users to design effective solutions.
  • Guide junior engineers and set engineering standards for the team.
  • Minimize detection and recovery time from incidents and ensure the team meets important metrics and SLOs.
  • Research innovative technologies and integrate them into our data infrastructure.
  • Do whatever it takes to make Xendit succeed.

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