Kata.ai

Data Engineer

Kata.ai

full-time

Posted on:

Location Type: Remote

Location: Indonesia

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Tech Stack

AirflowApacheAzureBigQueryCassandraCloudGoogle Cloud PlatformKafkaNoSQLPostgresSparkSQL

About the role

  • Design, build, and maintain scalable data pipelines, streaming infrastructure, and AI/ML data workflows that power data-driven products and enterprise AI solutions
  • Ensuring reliable, timely, and high-quality data is available across the organization
  • So that AI Engineers, Product teams, and enterprise clients can make accurate, insight-driven decisions and deliver intelligent customer experiences through Kata's AI and voice platforms

Requirements

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, Statistics, or related field
  • Relevant certifications (GCP Professional Data Engineer, Databricks, Airflow/Astronomer, etc.) are a plus
  • 1–2 years of professional experience in data engineering, software engineering with data focus, or a related technical role
  • Hands-on experience building or maintaining data pipelines in a production environment
  • Practical exposure to at least one streaming or batch processing technology (Kafka, Spark, or Airflow)
  • Familiarity with SQL and relational or columnar databases (BigQuery, PostgreSQL, Hive, or equivalent)
  • Exposure to cloud data services on GCP or Azure
  • Experience working in Agile/Scrum teams with sprint-based delivery
  • 3–5 years of professional experience in data engineering, with at least 2 years building and operating production-grade pipelines
  • Proven hands-on experience with Apache Kafka for real-time event streaming — including topic design, consumer group management, and at-least-once/exactly-once delivery patterns
  • Demonstrated experience designing and maintaining batch workflows using Apache Airflow and large-scale data transformations with Apache Spark
  • Experience working with BigQuery and/or Hive for large-scale analytics workloads, including query optimization and partitioning strategies
  • Hands-on experience with Cassandra or similar NoSQL wide-column stores for high-write or time-series data use cases
  • Experience supporting AI/ML data pipelines — feature engineering, training dataset preparation, or model inference data feeds
  • Experience with data quality frameworks and implementing data observability practices in production environments
Benefits
  • Flexible working hour for our employees
  • Learning experience in Conversational AI Industry
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
data pipelinesstreaming infrastructureAI/ML data workflowsSQLApache KafkaApache AirflowApache SparkCassandradata quality frameworksdata observability
Soft Skills
communicationcollaborationproblem-solvingdecision-makingorganizational skills
Certifications
GCP Professional Data EngineerDatabricksAirflow/Astronomer